Journal of Health

Science

Volume 2, Number 1, (Serial Number 2)January 2014

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Journal of Health Science

Volume 2, Number 1, January 2014 (Serial Number 2)

Contents

Public Health

1 Drug Addictions and Sexual Violence in Childhood and Adolescence: Analyzing Life Stories

Andréa Marques Leão Doescher, Andreza Marques de Castro Leão and Paulo Rennes Marçal Ribeiro

9 Aspects of Causality: A Verdict Inquiry of a Case with SSRI Use

Robertus Cornelus Brouwers, Anthonius Joseph Maria Loonen, Elisabeth Maria Carolina

Groenewoud-van Nielen and Tjoe Ing Oei

20 Indoor Surveillance of Airborne Fungi Contaminating Intensive Care Units and Operation

Rooms in Assiut University Hospitals, Egypt

M. Bassam Aboul-Nasr, Abdel-Naser A. Zohri and Enas Mahmoud Amer

Health Psychology and Pathophysiology

28 Decomposition of Surface Electromyographic Signal Using Hidden Markov Model

Angela Abreu Rosa de Sá, Alcimar Barbosa Soares, Adriano de Oliveira Andrade and Slawomir Nasuto

41 Development of Commonsense Knowledge Modeling System for Psychological Assessment in

Clinical Psycho

D.S. Kalana Mendis, Asoka S. Karunananda, Udaya Samaratunga and U. Rathnayake

56 Isolated Gross Hematuria or Associated to Acute Retention of Urine as a Sign of Urologic

Malignant Pathology

Angel Tomas Ibañez Concejo, Marco Antonio Castillo, Juan Sanchez-Verde Bilbao, Jorge Short

Apellaniz, Ambar Deschamps Perdomo and Joaquin Garcia Cañete

Journal of Health Science 2 (2014) 1-8

Drug Addictions and Sexual Violence in Childhood and

Adolescence: Analyzing Life Stories

Andréa Marques Leão Doescher, Andreza Marques de Castro Leão and Paulo Rennes Marçal Ribeiro

Department of Educational Psychology, UNESP—São Paulo State University, Araraquara 14805-292, São Paulo, Brazil

Received: October 14, 2013 / Accepted: January 16, 2014 / Published: January 31, 2014.

Abstract: The sexual abuse suffered in childhood and adolescence, in addition to damage to physical and psychological health of the victim, is considered as an important risk factor for alcohol and drugs addiction, development of psychopathology and psychosocial damage in adulthood. In addition to the pain and humiliation that are submitted by the abuse, children and adolescents also experience shame and guilt which require them to adopt coping strategies to endure those feelings. The use of psychoactive substances is a recognized way of dealing with the pains of living. This work, which is of narrative style, analyses and discusses, through five case reports, chemical dependency as a result of sexual abuse suffered in childhood and/or adolescence. The eight subjects in this study are male and have suffered sexual violence in this age period of life. Their ages range from 23 years to 39 years, and all are admitted to a therapeutic community in a city in the interior of Sao Paulo state, in Brazil, for treatment of chemical dependency, being met by the Department of Psychology. The reasons for the choice of the participants for treatment modality for patients are: difficult to stop using drugs, even unwilling to take it, they have easy access to it; the feeling of losing control over their lives; by successive losses as a result of drug use, and for fear that their lives had a tragic ending. With the exception of two participants, the others do not classify that as a child suffered sexual violence. However, all attribute that facilitated their entry into the world of drugs. Seven participants experienced such violence in childhood (between 7 years and 9 years) and adolescence (age 14). The attackers were people closed to the victims—in the case of two victims, their families, with the exception of one participant who was raped by a stranger. Six participants declared themselves as homosexual. Another participant does not claim to be homosexual, but presents difficulties in terms of sexuality. Two participants are HIV positive. The start of psychoactive substances use occurred during adolescence (12 years to 17 years). The participants see drugs as an anesthetic to the pain of the soul, a way to get pleasure, but they get charged expensively, as it increases the feeling of emptiness, guilt, helplessness, worthlessness and hopelessness. Although participants have sought help to deal with addiction, it is noted that throughout the life course the issue of sexual violence was not treated. It was noted that the patients have a double stigma in society: the issue of drugs addiction and the orientation of sexual desire, because the majority of participants are homosexual. The results reinforce the need for effective action geared to accommodate the victims of sexual violence and effective preventive measures to prevent children and adolescents from being abused. Key words: Sexual violence, childhood and adolescence, male gender, chemical dependency, sexuality.

1. Introduction

Sexual violence is a complex issue that has raised

room to problematize. Since the beginning of the

1990s, sexual violence against children and

adolescents is in evidence, and this is because society

is more sensitive to this matter [1]. An interesting

aspect that the researcher pointed is that growth of

intimacy, the appreciation of the intimate life and

Corresponding author: Paulo Rennes Marçal Ribeiro, Ph.D., professor, research fields: psychology, sex education and mental health. E-mail: paulorennes@fclar.unesp.br.

sexuality nowadays focus the look on trauma, and in

the psychological consequences of sexual violence,

because sex crimes generate psychic death, and it

breaks the identity of the victim.

There are various forms of sexual violence practices

against children and adolescents, among them:

prostitution, trafficking for sexual purposes, sexual

harassment, exhibitionism, voyeurism, sexual abuse,

pornography, among others. Note that the subject is in

itself large and complex.

Thinking about sexual abuse, you can set it as the

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Drug Addictions and Sexual Violence in Childhood and Adolescence: Analyzing Life Stories

2

participation of a child or an adolescent under 14 in

sexual activity that is not able to understand,

inappropriate to their age and their psychosexual

development [2]. In fact, all forms of sexual activities

in which children and adolescents do not have mature

conditions, cognitive and psychological to endure, and

that somehow violates the laws and social rules and

morals is considered abuse.

In the sexual abuse, the victim is physically forced

or emotionally coerced to participate in an intimacy

without necessarily having the emotion or cognitive

capacity to consent or judge what is happening [3].

Moreover, children are vulnerable to sexual assault,

because they rely on adults who are their benchmark

of what is and is not socially acceptable [4].

Summarizing, can be affirmed that sexual abuse is

the touch of the entire body, or parts of it, of children

or teens to satisfy sexual desire of older people (about

5 years minimum age difference), in which use power

to coerce them. It is indeed a crime that occurs in

different classes, in different cultures and ethnicities.

There is no ethnicity, religious belief, political or

social stratum immune to its occurrence.

According to the Brazilian Penal Code, the age

difference between the offender and the victim must

be greater than five years, so that the contact is

considered as sexual abuse [2].

Sexual abuse is not linked primarily to physical

assault; it may also be considered the caresses, kisses

and seductive words. It can also be the sensory

stimulation (pornography, obscene language sexy), the

touching of the child’s sexual organs, trial and/or

vaginal penetration, oral, anal and masturbation, as

well as induction of embarrassing situations for group

sex [5].

Sexual abuse includes a variety of acts from

caressing, touching genitals, breasts or anus,

voyeurism, exhibitionism, to the sexual act itself, with

or without penetration.

Sexual abuse may not involve physical contact, and

it can occur through open conversations and proposals

in order to instigate children’s sexual interest, or by

observing their intimate body parts, or even consist of

showing the genitals to them [4]. In addition, children

may be forced to watch pornographic movies and

pictures, physical contact can happen, caress, and even

vaginal, oral and/or anal sex. Finally, the previous

mentioned researcher, indicates that sexual abuse in a

child or adolescent is used as sexual gratification to

the rapist.

Sexual abuse is classified as in home, and out home

and institutional [1]. Out home abuse occurs outside the

family, usually being practiced by acquaintances of the

child and adolescent, who may be a neighbor, a

professional who assists the victim, among others. It is

usually a trusted person who is very close to the family.

There is also abuse in home, which occurs at the home

setting, involving people close to the victim or

caregivers, as: fathers, stepfathers, stepmothers, uncles,

grandparents, cousins, among others. Within this

classification, there is still institutional violence, when

it occurs in institutions that should take care of children,

for example, daycares, schools, and others. The in

home sexual abuse is the one that generates most

threatening and psycho-emotional implications [1].

The sexual abuse in home is any activity of sexual

nature in which the abuser has blood connection with

the victim [6]. According to those authors, this type of

abuse involves impacts psycho-emotional adjustment

difficulties such as emotional, feelings of guilt,

depression, isolation, relationship problems and

communication, and so forth.

Regarding to the sex gender of the victimized, it is

emphasized that the sexual abuse of children and

adolescent males are underreported, which promotes

the belief in society that the problem is not uncommon

[7]. Although many authors assert that most abuse

victims are female is important to note that this is still

an issue that needs to be discussed [1]. Authors also

expose that both girls and boys are vulnerable to this

type of child maltreatment [8]. In the case of males,

Schraufnagel et al. [9] mentioned that the childhood

Drug Addictions and Sexual Violence in Childhood and Adolescence: Analyzing Life Stories

3

sexual abuse of boys is not uncommon, with around

14% of men were sexually abused in childhood,

although this percentage can be significantly higher due

to the silence. In fact, the abuse can happen in

homosexual or heterosexual scenery.

Regarding to the implications of sexual violence

suffered, these reverberates on health, physical,

mental and social health of the victim, extending far

beyond the occurrence of abuse [7].

Moreover, the child or adolescent can make use of

PS (psychoactive substances) as a way of dealing with

the occurrence of sexual abuse. According to

Boruchovitch [10], psychological problems have

interrelationship with drug use, and people take PS as

a way to escape and be relieved from their problems,

the same occurring to teenagers.

The use of these substances in adolescence can be

classified into five motivational patterns: experimental,

for curiosity and adventure, recreational, social,

seeking pleasurable experiences to share with friends,

use circumstantial-situational, in which the adolescent

is motivated by the need of achieving a mental state in

some circumstance; intensified use, it involves the use

of long-term drug as a way to escape problems, and

finally, the compulsive use, where drugs are used with

high intensity and frequency, and such people, life

without such substances is empty and sad [10].

Thinking about vulnerable situations in which

children and adolescents victims of sexual abuse are

exposed, it is necessary to find ways to cope with this

problem, because they can make use of these

substances as an attempt to deal with difficult

situations such as: pain, suffering, shame, guilt, etc.;

and those feelings are very difficult to cope. It is

needed to think about primary prevention, before the

initiation to the use of PS.

There are three ways to prevent sexual violence,

which are: primarily: consists in the education of the

child so that they know their rights about their body

and that no one should touch them if them do not

desire; secondarily: early identification preventing

acts of abuse recur; thirdly: the prevention center for

rape victims in crisis, with full monitoring of the

victim and the aggressor [3].

However, these preventive measures are difficult to

put into practice, since many abuse victims decide to be

in silence because of the fear of the results of

confession. Moreover, when they do reveal, in general,

they are not given any support. And it is precisely in

these situations that they need to be more accepted. If

not, they may make use of PS and at some point in their

lives, look for treatment for Chemical Dependency.

To talk about prevention is needed discuss sexuality,

and not always as this subject is discussed on the

agenda which is the issue of sexual violence [1].

Indeed, beyond the violence a little issue addressed is

how the mental and physical effects that drugs cause

to users. And it is precisely because they are not

commonly treated subjects the school is called to

contribute to the discussion of these issues.

Thus, it is evident the importance of school geared

to discussing this matter with informative and

preventive approach preventive actions. Although

sexual violence is an embarrassing subject, it needs to

be questioned in the different social levels, between

those in school. In fact, the author explains that

students should be know how to identify any

suspected abuse situation, and whom to report to ask

for help, as well as sensitize them so that they realize

the harm that drugs bring [4].

Based on this, the study aims to analyze and discuss

the life history of drug addicts who have suffered

sexual abuse in childhood or adolescence and who are

currently in drug treatment in voluntary hospitalization.

2. Methodology

The study is a qualitative one. Qualitative research

works with values, beliefs, customs, ways of acting,

representations, opinions and trys to deepen the

complexity of facts and processes specific and

reserved to individuals and groups [11]. A qualitative

approach was employed for understanding phenomena

Drug Addictions and Sexual Violence in Childhood and Adolescence: Analyzing Life Stories

4

marked by a high degree of internal complexity.

Among the qualitative research, opting for the life

story is aim to capture what happens in the intersection

of the individual with their social environment [11].

The cited author elucidates that history of life can be an

instrument for analysis and interpretation, considering

that it incorporates subjective experiences combined

with social contexts, thus providing consistent basis for

understanding the individual component of the

historical phenomena. It complements that the story of

life is commonly taken from one or more designated

long interviews in which the interaction between

researcher and researched occurs continuously.

In summary, the history of life is a methodology

that is concerned with the relationship between

researcher and subject, thus contributing to a

committed, friendly and participatory listening,

remembering the story of the individuals which are

both the history of the team, that is, of the society of

which it is part.

2.1 Participants

Eight men, who experienced sexual violence in

childhood or adolescence, participated in the research.

Their ages range from 23 years to 39 years, and all

were admitted to a therapeutic community in the

interior of Sao Paulo, Brazil, for treatment of chemical

dependency, being met by the service of Psychology.

The reasons for the choice of participants by treatment

modality for inpatients are: difficult to stop using

psychoactive substance even unwilling, easy access to

its attainment, the feeling that they lost control over

their lives, by successive losses due to psychoactive

substance use, and the fear that their lives would have

a tragic ending.

2.2 Data Collection Instrument

The authors utilized semi-structured interview and a

diary, in which the interviews were recorded.

The semi-structured interview was chosen because

it opens the possibility for the interviewer to follow a

script and one can insert the same during the interview.

In this context, the interview, which was prepared with

the assistance of experts from the fields of Psychology,

Chemical Dependency and Sexual Violence,

encompassed the following items: sociodemographic

data, using SPA (substances already used, start using,

use evolution and treatments subjected), sexual

behavior (practical use of condoms in situations that

did not use the SPA and when use was made of this,

sexual intercourse after using SPA or concomitantly

with this, beliefs about sex and SPA), sexual abuse

(age the occurrence abuser (intrafamilial, extrafamilial,

institutional) circumstances in which it happened,

revealed that the victim and who, treatment received,

among others).

Having a field diary is a rich instrument, because you

can write down the relevant facts and circumstances,

which can be redeemed after the occurrence thereof. In

this paper, verbal and nonverbal behaviors (facial

expressions, psychomotor agitation, changes in voice,

among others) of the participants during the interviews

were recorded.

2.3 Procedure for Data Collection

Participants were contacted in the therapeutic

community through the Psychology Department of the

institution. So after the presentation of the work and

its goals for the psychologist in charge, and the

consent of the professional engineer and that the

therapeutic community, participants were contacted

and invited to participate in the study, and on this

occasion they were informed of the objectives.

Varying from two to three meetings a minimum

duration of 50 minutes each, which occur within the

affected community—then with the approval of them,

the interviews were scheduled. It is worth noting that

it was explained to them that these data would be used

for the preparation and disclosure of the present study.

2.4 Procedure for Data Analysis

The interviews and field diary were analyzed

Drug Addictions and Sexual Violence in Childhood and Adolescence: Analyzing Life Stories

5

qualitatively, and their contents grouped into

categories for analysis. The process for the categories

elaboration was based on the interpretation of the

content present in the speeches of the participants.

Bardin [12] stated that categorization is a sort of

organization operation of the constituent elements of a

set, doing differentiation and then by regrouping

analogically, aiming to simplify the representation of

the raw data.

In the content analysis, it has chosen the thematic

analysis, because it is more appropriate, since it focuses

on the identification of themes as registration units,

showing testimonials, comportment patterns, values,

beliefs, provisions that are found in the data collected.

3. Results

With the exception of two participants, the others

did not affirmed that suffered from sexual violence in

childhood or adolescence and, one of them stated that

it was “naughty since childhood” (sic). However, all

attribute that this favored their entrance into the world

of drugs.

The onset of substance use occurred in adolescence

(between 12 years old and 17 years old), through

alcohol; currently all of the respondents are crack

users, besides alcohol and tobacco.

Seven participants cited that suffered violence in

childhood (between 7 years old and 9 years old), and

adolescence (age 14). The attackers were people near

from the victims—in the case of two victims, their

families, except for one participant who was raped in

their adolescence by a stranger while returning from

school to home.

Participants did not tell their abuse to adults when it

occurred, due to: fear, shame, guilt, insecurity and

because they think their story would not be treated as

true. None of the participants even three of them who

have been hospitalized for treatment of chemical

dependency on other occasions were attended by

professionals to help them. One of the participants

said that he had never disclosed the abuse to anyone,

and that even being in the 9th admission to the

therapeutic clinic for drug users, this was the first time

that a professional approached the subject.

Two participants are HIV positive to HIV and both

believe they have contracted this disease through

unsafe sex.

Only one participant did not declare himself as

homosexual, but has conflicts about sexuality and

expressive shyness, and even having 23 years old, he

never dated and had consented sex.

Participants who declare themselves as homosexual

reveal significant mental suffering due to their sexual

orientation, because they feel “disobeying a sacred

law”—a heterosexual relationship, for “being in sin”

for “not being normal”, by difficulties faced for being

gay (believe life is harder for them), by family

conflicts due to their condition and doubt that God

loves them. In addition, all participants stated that if

they could choose, they would not be gay but

heterosexual.

Regarding the use of PS, the participants see drugs

as an anesthetic pains to the soul, a way to get

pleasures that afterwards will charge them expensively,

because it enhances the feeling of emptiness, guilt,

helplessness, worthlessness and hopelessness.

Their Dreams? “Being normal”, having a “normal

life” and be happy!

4. Discussion

Sexual violence is an unfortunate reality in today’s

context. However, it is necessary that the discussions of

theories be able to be effectively applied, so that the

alarming statistics of victims of abuse can be mitigated.

Therefore, it is necessary to articulate effective

strategies to stop this matter.

The results of this study highlight the need for

effective actions aimed to accommodate the victims of

sexual violence, and effective preventive measures to

prevent children and adolescents from being abused.

Incidentally, it is revealed the need for a thorough

evaluation of early interventions when one considers

Drug Addictions and Sexual Violence in Childhood and Adolescence: Analyzing Life Stories

6

the situation of abuse, because it is necessary to help

the teens not to use alcohol or other PS or have risky

sexual behavior. In addition, the Chemical Dependency

has been seen as a public health problem, since the

disastrous consequences have led to the Brazilian and

people from other countries.

A vast sex education can be a fruitful possibility.

With it, one can work different subjects, such as sexual

violence, and the orientation of sexual desire. Urge to

break with the stigmas and labels because it can not be

more accepted that children and adolescents are

physically and emotionally abused, being pushed to

make use of PS as a solution to their ills. Moreover,

they are targets of bullying because of their sexual

desire orientation.

Moreover, considering that sexual abuse in

childhood and adolescence is a risk factor to the

beginning of the use of PS in adolescence and

adulthood, it is important that professionals, especially

those who care for addicts, investigate this possibility,

so that these people are obviously treated and accepted.

Therefore, it is necessary to examine in detail the

possibility of using these substances as a way of coping

or escape the sexual abuse situation, especially in cases

where adult patients relapsed many times.

In summary, the results highlight the importance of

effective actions aimed to help the victims of sexual

violence, and effective preventive measures to prevent

children and adolescents from being abused.

Furthermore, the use of PS in adolescence can be

enhanced due to several factors, such as chaotic home

environment with parents who are PS users, with the

presence of violence (physical, psychological or

sexual) domestic, lack of dialogue and emotional

involvement between parents and children, lack of

clear rules of conduct and lack of parental authority;

dissatisfaction and failure to carry on their activities;

inappropriate shyness; perception of approval to the

use of PS by family, school, friends, or community;

insecurity; sensation of not belonging to anyone or

anything, the need for something concrete that allows

them to escape their problems and conflicts, even

temporarily [13].

According to the authors, “the young who is sad,

discouraged or even anxious, will look for things or

activities that help them to feel better. The effects of

drugs work temporally as a ‘remedy’ for their

problems: these teens will use drugs as an attempt to

get self-cured” [13].

Schraufnagel et al. [9] point to the risk of alcohol

use among survivors of sexual abuse in childhood and

adolescence. It is reiterated that the use of PS, in

general, is a way to escape from the problem of being

abused.

The issue of sexual abuse when not diagnosed and

treated on time can be a big gap for the use of PS by

the adolescent, since it is able to “numb” the pain of

the soul, is a problem that requires coping strategies.

Studies have shown that early use of alcohol and

drugs happens mostly in adolescence, and alcohol is

the most commonly used drug by adolescents [13]. It

is noteworthy that the onset of alcohol and drugs by

adolescents does not happen by chance, but reflects

the result of a “complex dialogue between risk factors

and protective factors, in which the adolescent is

immersed” [13].

The report of the first national survey on the

patterns of alcohol consumption in the Brazilian

population revealed that the onset for regular alcohol

use was 14 years old for boys and 17 years old for

girls. These data show that the use of PS is a serious

thing, and is considered a public health problem that

starts usually in adolescence.

The continued use of PS causes changes in the

structure and functioning of the brain, resulting in the

development of Chemical Dependency, which is

defined as a progressive, chronic and recurrent,

multifactorial, that goes beyond the phenomena

caused or triggered by drugs, covering also the

individual susceptibility and social context in which

the individual finds the substance [14].

In the present study, although participants have

Drug Addictions and Sexual Violence in Childhood and Adolescence: Analyzing Life Stories

7

sought help to deal with the Chemical Dependency, it is

noted that throughout the life course the issue of sexual

violence was not embraced and evidently treated.

The factors that contribute to the professionals

identify few men with a history of childhood sexual

abuse, and suggest that research in relation to this type

of violence in males by clinicians is little performed;

is belief by professionals that men do not tend to

reveal their experiences of childhood sexual abuse, the

consequences of disclosure are perceived as more

harmful than the consequences of non-disclosure,

because it happened in childhood and other

professionals may had met this demand [15].

Thinking about the adult who was sexually abused

in childhood, Dube et al. [16] pointed to the need of

having them identified and treated, because the

consequences of such violence do not cease upon

reaching adulthood.

Studies show that sexual abuse in childhood and

adolescence causes damage to physical and mental

health, leading to the development of mental and

behavioral disorders, sexual disorders, sexual identity

conflicts, issues regarding to sexual orientation, denial

and legitimization of abuse suffered in childhood or

adolescence, PS abuse, among others [7]. In general,

the findings also reveal a strong relationship between

childhood sexual experiences with the use of PS.

Furthermore, as the reports of the participants in

this study, sexual abuse suffered in childhood or

adolescence although legitimized by the victims,

outside silenced and seen as “something that should

not have happened”. The ambivalence is significantly

observed in participants’ speech, in which note the

fear, silence, anger and desire that everything had

been different.

It was observed that the subjects have a double

stigma in society: the issue of addiction and

orientation of sexual desire, as most of the participants

are gay.

Due to this, the attitude of society towards such

complex matters as the sexual abuse and the use of PS

was questioned. Often society is conniving, preferring

to be silenced than choosing to face in such matters.

However, considering to contribute to the fully

development of children and adolescents, these are

issues that need to be discussed openly with them.

Regarding to preventing sexual abuse, it is

necessary to talk openly about sexuality [1], and this

is unlikely, since this issue is not brought to children

and adolescents, and when the issue is talked, it does

not include the discussion about sexual violence. As

the researcher said: “thinking about possible solutions

to the problem of sexual violence involves, thinking

about children and adolescents as active-protect from

violence and abuse does not mean isolating them from

the world, but prepares them to deal with these

situations” [1].

It is important to emphasize that sexual violence is

a reality that haunts all of the different social classes,

ethnicities and cultures, and the adolescents are

exposed to PS, because access to them is easy. Do not

just say no to the use of these substances, teenagers

should be instilled the consequences thereof, and other

possibilities to resolve their conflicts.

Sex education is necessary to prevent sexual abuse,

because if the child has freedom and an affable

environment to talk about sexuality, she will feel free

to expose potential episodes of sexual abuse [4].

5. Conclusions

Sexual violence is a flagship issue in the current

context. Increasingly gaining ground in society is

questioned on various social levels. However, it is

necessary that the discussions of theoretical nature able

to be effectively applied, so that the alarming statistics

of victims of abuse can be mitigated. Therefore, it is

necessary to articulate effective coping strategies,

whereas the DQ is a public health problem, with

adverse consequences for the Brazilian population and

other countries.

The results of this study highlight the need for

effective actions to accommodate the victims of sexual

Drug Addictions and Sexual Violence in Childhood and Adolescence: Analyzing Life Stories

8

violence, and effective preventive measures to prevent

children and adolescents are abused. Furthermore, even

unveil the need for a thorough review of early

intervention when one considers the situation of abuse, it

is necessary to help ensure that adolescents do not use

alcohol or other SPA, or have risky sexual behavior.

A comprehensive and systematic sexual education

can be a useful possibility. Inside, you can work on

different subjects, such as sexual violence, and the

orientation of sexual desire. Urge break stigmas,

prejudices and taboos, especially because it can not be

more consistent that children and adolescents are

physically and emotionally abused, being pushed to

make use of the SPA as a solution to their ills.

Considering that sexual abuse in childhood and

adolescence is a risk factor to the use of SPA in

adolescence and adulthood, it is important that

professionals, especially those who watch addicts,

investigate this possibility, so that these people are

obviously treated and accepted. Therefore, it is

necessary to examine in detail the possibility of using

these substances as a way of coping or escape from the

situation of sexual abuse, particularly in cases in which

adult patients successive relapse.

Moreover, these professionals are instructed about

the signs that students who use SPA feature so that they

can make proper referrals, thinking of helping them. In

fact, it is necessary that these professionals are

prepared to address sexual education in the school

setting, because working with sexuality is also in the

preventive work of the students regarding sexual

violence and drug use.

Finally, the results highlight the importance of

effective preventive measures to prevent children and

adolescents are abused and both health professionals,

as education need to be aware of the dialogue of sexual

violence with substance abuse.

References

[1] T.S. Landini, O professor diante da violência sexual, São Paulo, Cortez, 2011.

[2] A.C.B. Maia, A.F. Maia, Sexualidade e Infância, MEC/SEF, Brasília, 2005, pp. 87-97.

[3] E.R. Gauderer, Abuso sexual na infância e na adolescência, Rio de Janeiro, Rosa dos Tempos, 1993, pp. 65-80.

[4] A.M.C. Leão, Estudo analítico-descritivo do curso de Pedagogia da UNESP de Araraquara quanto à inserção das temáticas de sexualidade e orientação sexual na formação de seus alunos, Ph.D. Thesis, Faculdade de Ciências e Letras da Universidade Estadual Paulista, Araraquara, Brasil, 2009.

[5] A.C.B. Maia, Sexualidade e deficiências no contexto escolar. Ph.D. Thesis, Faculdade de Filosofia e Ciências, Universidade Estadual Paulista, Marília, Brasil, 2003.

[6] M.A. Azevedo, V.N.A. Gerra, Crianças Vitimizadas: a Síndrome do Pequeno Poder, Iglu, São Paulo, Brazil, 2007.

[7] S.G. Arreola, T.B. Neilands, R. Diaz, Childhood sexual abuse and the sociocultural context of sexual risk among adult latino gay and bisexual men, American Journal of Public Health 99 (2) (2009) 432-438.

[8] S.R. Dube, R.F. Anda, C.L. Whitfielod, D.W. Brown, V.J. Felitti, M. Dong, et al., Long-term consequences of childhood sexual abuse by gender of victim, American Journal of Preventive Medicine 28 (5) (2005) 430-438.

[9] T.J. Schraufnagel, C. Davis, W.H. George, J. Norrisc, Childhood sexual abuse in males and subsequent risky sexual behavior: A potential alcohol use pathway, Child Abuse & Neglect 34 (5) (2010) 369-378.

[10] E. Boruchovitch, O uso e abuso de drogas na adolescência, 2nd ed. Petrópolis, vozes, 2000, pp. 192-204.

[11] M.A.S. Paulito, A pesquisa qualitativa e a história de vida, Disponível em: http://www.uel.br/revistas/ssrevista/c_v2n1_pesquisa.htm (accessed in Sept. 25, 2012).

[12] L. Bardin, Análise de conteúdo, Lisboa, Edições, 1977, p. 70. [13] E.A. Silva, D. Micheli, Adolescência, uso e abuso de

drogas: uma visão integrativa, São Paulo, Unifesp, 2011. [14] M. Ribeiro, R. Laranjeira, O tratamento do usuário de

crack, Porto Alegre: Artmed, 2012. [15] W.C. Holmes, G.B. Slap, Sexual abuse of boys: definition,

prevalence, correlates, sequele, and management, JAMA 280 (21) (1998) 1855-1162.

[16] S.R. Dube, R.F. Anda, C.L. Whitfielod, D.W. Brown, V.J. Felitti, M. DONG, et al., Long-term consequences of childhood sexual abuse by gender of victim, American Journal of Preventive Medicine 28 (5) (2005) 430-438.

Journal of Health Science 2 (2014) 9-19

Aspects of Causality: A Verdict Inquiry of a Case with

SSRI Use

Robertus Cornelus Brouwers1, Anthonius Joseph Maria Loonen2, Elisabeth Maria Carolina Groenewoud-van

Nielen1 and Tjoe Ing Oei1

1. Faculty of Law, University of Tilburg, Tilburg 5037AB, Netherlands

2. Faculty of Mathematics and Natural Sciences, University of Groningen, Groningen 9747AG, Netherlands Received: July 05, 2013 / Accepted: December 16, 2013 / Published: January 31, 2014. Abstract: Sometimes more than one expert advises the court. They use different notional frameworks in doing so, and may report different opinions about the case they examined. In this case, the authors discuss the relation between the use of a SSRI (serotonin reuptake inhibitor) and a fatal tragedy in a family where the mother was accused of killing her husband and daughter a few days after use of the SSRI. No fewer than seven experts were heard (four behavioral experts, one behavioral toxicologist, one pharmacist and one pharmacologist) at the ensuing trial, and various possible diagnoses were dealt with in the experts’ reports and at trial. More attention must be paid to the mentally debilitating influence of SSRI medication on certain psychological functions shortly after its intake. Although a mono-causal relationship between that influence and the accused’s intention is necessary to exculpate the accused from guilt, the authors believe that a singular connection is never happened in the case. Keywords: Violence, medication, causality, judgment.

1. Introduction

The effects of a drug on behavior can be disastrous,

but as presumed, in only very rare cases is there a

causal relation between the drug in question and a

violent act, fortunately.

As more scientists participate in criminal trials,

greater clarity about the circumstances or the cause of

a violent offence does not automatically result.

Amongst other things, this has to do with the

interpretation of the facts by various disciplines, each

with their own professional thought patterns, methods

and testing procedures. For the court to be able to get

an overall impression, it must at least be aware of the

methods of the various expert witnesses and actors

(such as the public prosecutor, the accused, behavioral

experts and medical specialists) in order to

meaningfully integrate the evidence and arrive at a

Corresponding author: Robertus Cornelus Brouwers, M.D.,

Ph.D., research field: forensic psychiatry. E-mail: brour@xs4all.nl.

legal conclusion or verdict. Here, a case was discussed

which several experts were heard in a court

proceeding, who each reported to the court from their

own notional framework, and from which the court

had to arrive at a verdict in relation to the facts and

opinions offered.

Oei [1] stated the notional frameworks that the

various parties use during the trial are different. In his

opinion, the legal, the behavioral and the judicial

relationship frameworks were applied. Starting with

the judicial framework, the following issues are

relevant: offence, possible disorder and danger of

re-offending and possible treatment. Note that the

accused often (erroneously) thinks that there is no

disorder whatsoever. In those cases, however, it is

possible to discuss the desired treatment with the

accused. Also, the accused scores positive points with

the court if he shows willingness for treatment. In this

way the accused hopes to escape an unconditional

prison sentence or court order, and instead, “to get off”

DAVID PUBLISHING

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Aspects of Causality: A Verdict Inquiry of a Case with SSRI Use

10

with a suspended sentence with an added condition of

being treated by an institution or expert appointed by

the court. Furthermore, if the accused does not have a

disorder, the court cannot attribute the possible danger

or re-offending to one. For, without a disorder there

can be no unaccountability and no exemption of

culpability.

The lawyer has a slightly different perspective from

the accused, as follows: possible offence, possible

disorder, danger of re-offending if there is a disorder,

accountability, and meting out of punishment. Also, the

alleged facts of the offence must first be legally proven,

assuming they give rise to a punishable offence.

Next, the behavioral expert’s framework takes into

account the following considerations: possible

disorder, then the relationship with the possible

offence, determination of accountability, possible

danger of re-offending as a result of the disorder, and

possibilities for treatment.

In determining an accused’s accountability, the

following questions must be answered from the

behavioralist’s perspective: is there a pathological

disorder at the time the punishable offence was

committed? If yes, is the causal relationship between

the disorder and the punishable offence adequately

plausible? Again, if yes, how should the

accountability be assessed in the light of the first two

questions and all circumstances of the case? The

presence of a disorder contributes to recidivism in the

behavioral expert’s point of view; however, the

question of recidivism is only asked if the question

about a relevant disorder has been answered in the

affirmative.

Before Oei’s work, Brouwers et al. [2] had already

concentrated on the question of whether medication

can have undesired effects, or may even give rise to

violent behavior. As far as the authors know there is

no drug that always causes violence in everyone who

takes it. Moreover, some people are always prone to

violent behavior when they take a certain drug, as is

the case for instance with alcohol. Furthermore, some

drugs sometimes produce a temporary change in the

psychological condition of some people. If during that

period something happens—a threat, or a provocation,

for example—the person can respond with violence.

Still, one needs a possible victim to commit a violent

crime.

To elaborate upon the last point, consider the

following. A SSRI (serotonin reuptake inhibitor) can

produce a temporary state of depersonalization. If,

during that period a man is unexpectedly and suddenly

dismissed from his employment, he may become so

angry that he wants to kill his boss. Normally he will

not do that, but then, in this state of depersonalization

he goes to the house of his boss and is ready to shoot

him. The boss is not at home and while the man is on

his way back the depersonalized state disappears and

he asks himself, “What am I doing?” It is realistic to

say that probably in most of the cases there no violent

act during the temporarily changed condition because

there was no opportunity, or no possible victim. But

there can be a causal relation if both circumstances

exist. By taking the medication a temporary disorder

may occur, causing the person to behave differently

than usual, but without that particular drug there is no

disorder or no offence, nor any danger of re-offending.

In the end the violent behavior is the result of chance.

If, for instance, ten thousand people use that drug,

perhaps a thousand of them will temporarily

experience depersonalization, a hundred of them will

experience a serious life event during the

depersonalization, and ten of them will want to react

with violent behavior towards that event, five will

have a possible victim available as well, and finally,

one will produce a victim. Different levels of damage

will result in the one instance, depending on how the

victim responded to the threat.

In relation to a real case, which concerns a

well-considered, instrumental form of violence, the

question arose whether a drug, in particular, an

anti-depressant (an SSRI) can cause a temporary

mental disorder leading to a violent offence.

Aspects of Causality: A Verdict Inquiry of a Case with SSRI Use

11

2. Methods

To illustrate the different processes as illustrated in

an actual case report, a search was done in the

Netherlands’ verdict register. This register is freely

accessible to the public. Because it is essential to go

step-by-step in time to ascertain if the perpetrator

knew, or could have known, what the consequences

were of taking this kind of medicine the following

search criteria were used: use of an SSRI during

violent act, start of SSRI use no longer than four

weeks (prior to the violent act), the verdict must

contain enough facts and multidisciplinary

contributions, and the violent act having occurred as

recently as possible to complement discussions of

other, past cases. Applying these criteria, four cases

were found, but only one case provided sufficient

facts to formulate the within analysis.

Also, in order to determine if there is any reason to

believe that there could be a relationship between

(recent) use of SSRI and violence the literature on this

topic was reviewed and summarized.

3. Results

3.1 Description of the Case

The woman had been suffering from bouts of

depression since 1996, for which she was treated with

medication each time. Specifically, since 2003, she

had been prescribed the drug paroxetine (an SSRI).

She also suffered a sub-arachnoid haemorrhage, the

exact location of which was never determined. In June

2008 she was in a seriously depressed state once more,

and on 6 August of that year, she was prescribed

paroxetine again, 20 milligrams once daily. The

woman did not fill this prescription. When she

consulted the physician she had discussed whether she

needed psychological aid. Her daughter very much

wished the woman would accept this kind of

assistance. She had promised her daughter she would

agree to this kind of treatment, but only after

discussing it with her own GP, which was the reason

why she had not yet taken the prescribed drug. On 3

September 2008, she consulted her own GP, and as in

the meantime there had been no improvements in her

depressive complaints, and the prescribed dose of

paroxetine was augmented to 20 mg twice daily.

Arriving home, she started at once with three tablets

of paroxetine and also two tablets of oxazepam, for

unknown reasons. The following day she took two

more pills of paroxetine, but no more oxazepam.

The night of 4 and 5 September, after midnight, the

woman met her daughter at Schiphol Airport,

Amsterdam. Her daughter asked the woman about her

discussions with the GP and the woman said that she

had chosen the drug and not the psychological

assistance, unlike her earlier promise to her daughter.

The daughter got very cross with her mother. This

conflict created a bad atmosphere in the home, and

after her husband and her daughter had gone off to bed,

the woman was very shaken and sad.

She sat on her settee and experienced an

overwhelming feeling that she did not want to live any

more. At the same time she felt that she could not

cause the grief that her suicide would inflict upon her

husband and daughter, and so she decided to take

them with her in death. She then made fairly extensive

preparations of her farewell and subsequently went

looking in the home for a means by which to kill them.

She found an axe in the garage. The woman struck her

husband in the head several times with the axe, and

then thought, “Two more to go”, meaning herself and

her daughter. After having killed her daughter with the

axe as well, she tried to commit suicide by running her

car into a tree. She had by then already called the

emergency number (at 4.59 a.m.) and announced that

she had committed murder. The woman was wounded

in the collision with the tree and was taken to hospital.

At 9.05 a.m. (5 September), blood samples were taken,

which were later analyzed by the NFI (Dutch Forensic

Institute). In the blood, traces (< 10 ng/mL whole

blood) of paroxetine were found.

There are plenty of questions concerning this case,

Aspects of Causality: A Verdict Inquiry of a Case with SSRI Use

12

for instance: what is the function of paroxetine in the

violent acts? Is it a dominant, monocausal, or

contributory (facilitating) function? Is the contribution

of paroxetine dose-dependent? How quickly do

changes occur? Can a temporary mental disorder be

caused by it? Are there differences in result where the

violence is impulsive or instrumental?

3.2 SSRIs and Violence

By open discussions of cases, such as the one just

described, attention is drawn to important, hitherto

unknown side effects of drugs [3]. Whether there is

indeed a causal relationship between the use of the

drug and the phenomenon observed cannot be directly

deduced from this, however. That said, scientifically

proving causality is not essential: rather, identifying

the possibility for suicide and violence brings about

attentiveness after the drug in question has been

prescribed. Only very rarely do the opinions of the

various experts contrast. Such contrasts, however, do

occur in the question of whether anti-depressants in

general, and SSRIs in particular, may give rise to

suicide and violence. Reports highlight an additional,

complicating factor, that is, that especially children

and young people are susceptible [4-6].

Healy et al. [7] described a possible relationship

between SSRIs and violence. In addition, SSRI stories

[8] listed over two hundred cases in which a relation

between murder, suicide and an anti-depressant was

suggested. Lareb [9] identified that, until June 2009,

24 cases were reported to the Dutch Side Effects

Centre in which the use of an SSRI and aggression

coincide (8 cases of Paroxetine, 5 cases of Citalopram,

4 cases of Fluoxetine, 4 cases of Fluvoxamine, 2 cases

of Escitalopram and 1 case of Sertraline). They

suggested a possible relation between SSRIs and

aggression. Europe Eudravigilance [10] reported 700

serious cases and WHO data also supported the

association. Special attention should be given to this

association, considering the nature of the adverse drug

reaction and the possible consequences. Thus, the

relationship between SSRIs and violence (suicide,

homicide) cannot be excluded.

In spite of these reports the chance of violence

(suicide, homicide) being brought about by the use of

anti-depressants must be considered to be extremely

small [11-14]. But this does not necessarily mean that

this relationship is negligibly small in individual cases.

And there is understandable issue as to whether the

risk is “not demonstrable” and “non-existent”.

It has not been proved that the use of an SSRI may

give rise to an aggressive incident, but it is plausible.

This is in line with knowledge gained by general

experience, that is, that the use of psychoactive

substances (the best known example is alcohol) may

give rise to incidents of aggression. SSRIs are

psychoactive substances and they affect the nature and

the intensity of emotional processes (e.g., anger). Thus,

it is possible that under certain circumstances SSRIs

contribute to the occurrence of an aggressive incident.

By this the authors mean that the use of the

medication plays an important part in the occurrence

of the incident under prevailing conditions and at that

particular moment. Without the use of the drug, the

occurrence of the phenomenon, e.g., aggression,

outburst of anger, outburst of violence, emotions

running amuck, etc., would have been considerably

less likely. What is the mechanism that triggers the

aggression?

The initial idea was that aggression was the result

of disinhibiting suicidal impulses: a depressive

disorder goes together with suicidal desires and plans,

but also with inhibitions, which stop the suicide from

taking place. By treatment with anti depressants the

activity, energy level of the patient improve, before

improving his mood. Because inhibitions disappear,

some people commit suicide during the first phase of

the treatment. The biochemical explanatory model

pointed to the consequences of various kinds of

neurotransmission (adrenerg and serotonerg). The

adrenerg effect was thought to be especially important

for the impulse (drive) and the serotonerg for the

Aspects of Causality: A Verdict Inquiry of a Case with SSRI Use

13

mood. Later this is turned out to be too simple for a

rendition of the facts. The serotonerg system plays a

part in mood, that is, fear as well as aggression. Even

a distinct serotonin-dependent subtype of depression

has been postulated, in which aggression is the first

symptom [15]. In other words, SSRIs appear not just

to influence mood. Also, SSRIs cause mental

deregulations, such as a withdrawal symptoms, during

the initial phase of treatment or after the treatment has

been stopped. Quite soon after starting treatment in

some people, an increase of fear phenomena like

increased jitteriness, impulse outbursts, fear of dying

occur. Such symptoms may also occur after a sudden

end of the treatment. People might become aggressive

as a result of this feature of treatment with SSRIs.

A second possible explanation for the occurrence of

(auto) aggression after the start of the treatment with

SSRIs is side effects such as akathisia, which is the

urge to move about and feelings of unrest, unwellness,

inner unrest, or depersonalization. There are various

ideas about the method through which akathisia

triggers aggression. Loonen and Stahl describe a

biological mechanism in which akathisia is basically

an artificial form of being motivated to get moving

[16]. The patient is uncontrollably provoked into

executing certain (aggressive) behavior. Another idea

is that akathisia constitutes a torment to such an extent

that people in their desperation become (auto)

aggressive. This side effect is typical for

anti-psychotic medications, but is a regular feature of

SSRIs [17-19], for instance, with fluoxetine showing

an incidence rate of between 10% and 25%. Akathisia

is also a symptom of a serotonerg syndrome featuring

mental phenomena such as restricted awareness, (auto)

aggression, neuromuscular phenomena and

autonomous instability.

In an attempt to illuminate the mechanism of

SSRI-induced aggression, two forms of animal

aggression are relevant: defense and hunt (or, assertive)

aggression [20]. Of these two forms of aggression

there is an example in rodents where administering

anti-depressants had the opposite effect, namely, the

inhibition of defensive aggression and the promotion

of assertive aggression [21]. It is postulated that in

order to initiate these two forms, there is in principle

an emotional, affective or “hot” form of aggression as

well as a cognitive, instrumental or “cold” one. The

emotionally initiated form shows strong resemblance

to the fear reaction and is triggered by the amygdala,

or the almond core of the brain, where the emotional

component (anger) is primaryily triggered. On the

other hand, the cognitive one which initiated form of

aggression results from a careful analysis of the

circumstances is both initiated and controlled by the

prefrontal cortex of the brain (or PFC). The emotional

component (desire) is secondary in this case.

The situation in man is more complex than for

instance in the cat [20] or the rat [21] on account of

mankind’s far greater linguistic skill. In man all

sensory information can be replaced by language

symbols and aggression can be expressed entirely in a

linguistic way. Because of this, and because of the

wider development of the prefrontal brain, the

instructiveness of the cognitive control is greater. In

this explanatory model the inhibition of the emotional

response and the promotion of the cognitive response

are functions of a certain area of the brain, the medial

prefrontal cortex [22]. To put it simply: various parts

of the brain affect each other’s functioning [23].

The complex serotonerg system affects these

structures. There are connections from the brain stem

to all of the brain structures that were mentioned

before. And, in order to achieve its effects, no fewer

than 14 different types of receptors [24] are used, four

of which are associated with the regulation of

aggression. When the system is repeatedly

over-stimulated, the receptors’ sensitivity adapt and

change what happens as a result. It is supposed that

SSRIs stimulate aggression by inhibiting and

stimulating various brain structures, with three

different types of responses occurring simultaneously:

dysphoria (feelings of unease), the facilitation of the

Aspects of Causality: A Verdict Inquiry of a Case with SSRI Use

14

hot (emotional) aggression response and the

facilitation of the cold (cognitive, instrumental)

aggression response.

To sum up, there are indications that SSRIs may

have a causal relationship with aggressive violent

behavior, namely, by reducing inhibitions in a

depression, by side effects such as akathisia and

depersonalization, and by inhibiting as well as

stimulating certain areas of the brain, thus promoting

the emotional and the cognitive aggression response.

4. Discussion

4.1 The Importance of the Concentration of Paroxetine

According to the court’s verdict in 2008, the locum

had once again prescribed paroxetine to the woman, in

a dose of 20 milligrams (1 tablet) once daily, but she

did not fill the prescription. This was confirmed by the

fact that the prescription was recovered in the

woman’s home, and also by the pharmacy’s records,

which showed that no medication had been delivered

to the woman between 17 December, 2007 and 3

September, 2008.

In the consultation with her own GP on 3

September 2008, the dose was augmented because the

GP had supposed that the 20 milligrams per day had

not been effective. Had the woman started her

medication on 6 August 2008, she would have been

taking one tablet of the drug daily for 4 weeks, and

there would not have been any improvement after 4

weeks’ medication. (According to the standard GP

guideline (Dutch General Practitioner Association,

depressive disorder, M44, 2003), when insufficiently

effective, the dose should be doubled after four to six

weeks).

The woman later testified that she had taken three

tablets of paroxetine on 3 September and two more on

4 September.

The toxicological analysis by the NFI (Dutch

Forensic Institute) showed traces of paroxetine in her

blood and concluded that the concentration was so

low that it could not have influenced her behavior. But

later, during the trial, pharmacological experts agreed

that the conclusion was wrong in several respects. On

the basis of one single measurement of whole blood,

taken quite some time after the drug has been ingested,

it cannot be determined how high the concentration

was shortly after taking the drug. Furthermore, in the

use of serotonin reuptake inhibitors (occasional) cases

are known where normal short-term use was followed

by an outburst of violence.

If violence, as a side effect of an SSRI, is linked to

the presence in the blood of a relevant quantity of the

serotonin reuptake inhibitor [25] then the woman’s

violent behavior could be explained by the use of the

drug. It should be added that only in those cases when

at the time of the actions the accused lacked any

insight into the scope of her actions, and their possible

consequences, such a situation could lead to acquittal

because intent is lacking. Such cases are rare because

evil intent cannot be proven as in conditional intent

cases. It must be evident that she did not know and

could not know that such consequences might result

after taking the drug. However, usually an accused has

some insight in the scope of his actions, and legal

practice shows that in such cases a (lack of) intent

defense is often unsuccessful.

Sometimes the intent defense is unsuccessful,

because an accused’s “own culpability” is taken as the

starting point in law. Intent is then assumed on the

basis of culpa in causa. “Own culpability” might be

assumed if it is determined that the accused has taken

more medication than was prescribed, and that he also

is aware, or can be aware, that a higher dose might

lead to committing violence.

If, in the case being discussed, the woman took

three tablets on her own accord, because she thought

that “there was no harm in that” and also that she has

not heard or read anywhere that there could be harm in

doing so, “own culpability” is out of the question. But

if the woman knew about or was aware of this side

effect, that is, that violent behavior may occur, then

ingesting the (3 tablet) dose can be seen as “own

Aspects of Causality: A Verdict Inquiry of a Case with SSRI Use

15

culpability”, and intent can be assumed. The

discussion during the trial would then probably be

whether or not the side effect is a rare one. If the side

effect hardly ever occurs with users of the drug, it is

reasonable for the defense to plead that “own

culpability” is out of the question. When the

concentration in the blood is of no importance and the

woman never had a similar reaction in previous

treatments, taking three tablets instead of the

prescribed two cannot be held against her in relation

to the violence against her daughter and her husband

[26]. Finally, whether the woman’s previous

sub-arachnoid haemorrhage made her more

susceptible to an undesired effect of paroxetine is also

questionable, but in other cases of violence and the

use of serotonin reuptake inhibitors no descriptions of

a similar affliction were found.

4.2 The Importance of a Delusion

In this case the violence was disproportionate and

of an instrumental nature, in which the actions were

prepared over a period of several hours. This could be

explained by a state of delusion in which reality is

distorted. It is well known that in a paranoid

delusional state, a situation is perceived as threatening

or dangerous when in reality there is no threat or

danger. The woman’s decision to commit suicide and

to resort to violence towards her husband and daughter

was perhaps impulsively colored after the argument

with her daughter. It is known that negative aspects

receive more attention during a depression, and in this

case, the negative aspects may have been

overemphasized in the argument between mother and

daughter, causing the woman’s judgment to be

ultimately impaired. But once her decision was made

obviously there was nothing that could make her stop.

No fewer than seven experts were heard (four

behavioral experts, one behavioral toxicologist, one

pharmacist and one pharmacologist) and various

possible diagnoses were dealt with in the reports and

during the trial: delusion, psychosis, delirium,

depression, recurrent depression, intoxication,

personality disorder, depersonalization, restricted

awareness, lowering of barriers, paradoxical reaction,

triggering effect, fear, primitive defense and coping

mechanism, suicidality, tunnel vision, subarachnoid

hemorrhage, organic brain disease, psycho-toxic effect.

With so many differing expert opinions, it is difficult

for the court to find its way through this maze, making

this review appropriate. Because this case concerned a

well-considered instrumental form of violence,

psychopathological conditions that are associated with

this kind of violence as psychosis (delusion) or

depersonalization enter the picture. In

depersonalization, feeling is divorced from cognition

and apparently businesslike actions are possible [27].

Reasons for the occurrence of depersonalization are

severe stress on account of the argument with her

daughter, sleep deprivation because of staying up into

the small hours, and the use of the SSRI.

The accused’s conviction to kill herself as well as

her daughter and husband may be qualified as a

psychotic condition within the definition of Van der

Waard [28]: a delusion could best be described as a

shuttered unfalsifiable conviction with which the

patient feels emotionally related and which is deemed

implausible by most others because of the

unshakeable certainty with which it is expressed. In

the trial the woman testified that she had repeatedly

struck first her husband and then her daughter

forcefully in the head with an axe in the early hours of

the morning, and that this was the only way for her to

do any justice to herself and her family members. The

verdict does not refer to the concussion she suffered as

a result of running into the tree, and she could

obviously remember everything quite well.

There can be no question of intent, if a person lacks

any insight in the scope of the actions and their

possible consequences, as is the case with when

someone acts in a state of delusion. The woman’s

attorney maintained that she could not freely exercise

her will and that she had been deprived of any insight

Aspects of Causality: A Verdict Inquiry of a Case with SSRI Use

16

in the scope of her actions and their possible

consequences because her mental condition at the time

of her deed was seriously impaired. According to the

court, however, the experts did not agree on the

existence of a delusion, psychosis, delirium or similar

condition. They did agree, though, on a recurring

depression, but not that it was a psychotic depression.

The experts did not answer the question whether

paroxetine can cause a delusion or whether during a

delusion the use of paroxetine can produce or promote

violent behavior.

4.3 The Affliction, the Drug and the Deed

Separate from the framework, from which the

various parties to court proceedings approach the

offence (see the Introduction, above), whether the

affliction, or the drug, or both play a part should be

addressed. As such, it should be determined whether

an accused’s actions take place under the influence of

paroxetine because it can change certain psychological

processes. The use of paroxetine may affect

neurophysiologic functions and normal thought

patterns. Accordingly, in the case being reviewed the

woman’s thoughts that she did not want to inflict the

grief of her suicide on her husband and daughter and

that she had to take them along, could not be tested

against the social norm: it is not acceptable to kill a

fellow human being. The woman herself testified that

she took paroxetine in the days preceding her act, and

indeed, a low concentration of the drug was found in

her blood. Even with low concentrations of paroxetine

(or other serotonin reuptake inhibitors) there are cases

in which (short term) use was followed by violence

and suicide during the first week of the treatment. See,

for instance, the case of Joseph Wesbecker, who, in

the morning of 14 September 1989 in Kentucky, USA,

shot twelve people while using a serotonin reuptake

inhibitor.

In the case being discussed, the woman had both

the time and the opportunity to reflect on and to

account for the consequences of her intended actions.

It is remarkable that, in the period she was preparing

her actions, the horrible nature of her intentions did

not make her change her mind. Apparently she was

convinced that her actions would spare more grief.

The question is whether she did register the appalling

nature of her intended actions as such because of the

paroxetine affected certain areas of the brain that

typically have a corrective effect on such violent

thoughts.

There are indications that SSRIs affect

neurocognitive processes. For instance, Almeide and

his colleagues [29], found that citalopram (a serotonin

reuptake inhibitor) had a negative effect with healthy

men on “contextual processing” tasks. The result was

a temporary anomaly in being able to discriminate

between new and familiar objects within 24 h after

taking an anti-depressant. Similarly Harmer and her

colleagues [30] found that healthy volunteers, with no

history of depression, showed a diminished response

in certain areas of the brain to pictures displaying a

threat. What made this research special was that the

time in which the picture was displayed was so short

that the testee was not aware of the threatening

content, and that, nevertheless, after the use of

citalopram the areas of the brain in question responded

less fiercely than without the use of citalopram. With

people with a depression and a single dose of

citalopram, the pictures with scary portrayals were

perceived less fiercely [31].

To sum up, in certain persons with a depression, in

the first few days of their treatment with an SSRI

neurocognitive processes may be affected in such a

way that feedback of intended behavior is diminished,

the SSRI quite possibly has a contributory effect.

4.4 Assessing Causality

Another question to consider is whether the

different players’ frameworks with which they

approach the legal proceedings could lead to a

different result? For example, the accused’s lawyer

looks at the accused’s action(s) as his starting point. In

Aspects of Causality: A Verdict Inquiry of a Case with SSRI Use

17

the case being reviewed, the woman’s attorney argued

that in view of her mental condition the woman should

be found completely unaccountable and that her

condition did not fit an assumption of premeditation.

The court rejected this argument in its deliberations

because, even if her action(s) were not to be attributed

to her at all, this does not automatically lead to the

conclusion that she was unable to act with

premeditation or that the violent actions were not the

result of an immediate impulse that caused her to act

without delay. The circumstances outlined by the

court showed that the accused had the time and the

opportunity to consider and to account for the

consequences of her intended actions. The question,

though, is whether all of this happened while the

woman was experiencing a pathological condition?

In court proceedings, the behavioral expert takes the

disorder as his starting point. In this case the violence

is instrumental, and accordingly, syndromes that may

explain instrumental violence must be demonstrated

or excluded. Earlier akathisia, depersonalization and

delusion were mentioned, but depression is also of

importance as SSRIs may have a causal relationship.

The effects of SSRIs have been mentioned by

experts, such as a boosting effect or a barrier- (or

inhibition-) lowering effect, but these were not

considered to be likely explanations for a violent

effect of the kind such as was perpetrated by the

woman.

Depending on the experts’ advice to the court, a

wide range of possibilities may be presented, which

only enter the picture when a disorder is suspected and

when that disorder is linked to the facts of the

accused’s charge.

When paroxetine has an unknown, recorded, direct

effect (manifesting in distortions of perception,

cognitive distortions, depersonalization, akathisia), but

is not dose-dependent, the woman could have been

acquitted because intent is lacking. But if the effect

was turned out to be dose-dependent and she was

aware or could have been aware of such effects,

culpability, or culpa in causa, enters the picture: it

may be an unintended or unpursued effect, but

nevertheless it is the result of taking more than

prescribed.

If, as an element of the disorder, a (temporary)

delusion exists caused by the SSRI medication, then

complete unaccountability can be put forward,

resulting in no criminal disposition. If that is not the

case, and only the depression contributes to the action,

the woman could be held only partly accountable.

Should the chance of re-offending be deemed small,

detention in a mental hospital remains, as typical

punishment. A treatment order alone could still be a

possibility because the court might decide to impose a

conditional sentence, with the specific stipulation that

the accused undergo treatment. The woman’s

preparedness to undergo treatment could be discussed

in the court. Perhaps, in complex cases such as this, it

is advisable for the public prosecutor and the defense

attorney to avail themselves of the opportunity (since

the introduction of the Act Experts in Criminal Cases)

to have pre-trial deliberations with the magistrate

about which additional questions regarding what

content should be provided with in the report pro

justice.

5. Conclusions

It is extremely difficult to find actual cases in which

a person, by taking a drug prescribed by his doctor,

acts in a (lethal) violent manner. When answering the

question in this case as to whether that possibly

exempted the woman from guilt, the court concluded

that her accountability was lessened to a certain extent,

in agreement with the experts’ conclusions. However,

the court also found that it had not been determined

which element was exactly responsible for this, and to

what extent, and that no circumstance had been

deemed likely to exclude culpability completely.

This verdict is acceptable to the authors, because no

single factor is monocausally related to the offence.

However, in their opinion, greater value should be

Aspects of Causality: A Verdict Inquiry of a Case with SSRI Use

18

attached to a contributory psycho-toxic effect from the

use of medication (SSRIs) and to the disordered

judgment and critical thinking that go along with the

resulting (temporarily) psychopathological condition.

Finally, the various parties to the proceedings should

be aware of, and should keep in mind the different

notional frameworks they use during criminal trials.

Acknowledgments

The authors thank Prof. Kees van Grootheest, from

the University of Groningen, Netherlands and

Anthonie Wijnberg, lawyer at Groningen, Netherlands

for their contributions to this paper. The authors also

gratefully thank S. Grace Kerr LLM, BSc (OT)

London, ON, Canada, for her critical review and

support.

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Journal of Health Science 2 (2014) 20-27

Indoor Surveillance of Airborne Fungi Contaminating

Intensive Care Units and Operation Rooms in Assiut

University Hospitals, Egypt

M. Bassam Aboul-Nasr1, Abdel-Naser A. Zohri2 and Enas Mahmoud Amer2

1. Faculty of Science, Department of Botany, University of Sohag, Sohag 82524, Egypt

2. Faculty of Science, Department of Botany and Microbiology, University of Assiut, Assiut 71515, Egypt

Received: January 01, 2014 / Accepted: January 16, 2014 / Published: January 31, 2014. Abstract: Mycoflora of atmospheric air and dust samples collected from air conditioning systems in 12 of each I.C.U. (intensive care units) and O.R. (operation rooms) were tested using settle and dilution plate methods on four types of agar media and incubated at

25 °C. Forty-five fungal species representing 23 genera were isolated and identified. The most prevalent genera recorded were Cladosporium, Aspergillus, Penicillium and Fusarium. The total colony forming units of airborne fungi recovered in I.C.U. and O.R. ranged between 31.13-49.61 colonies/m3 on the four types of media used. The fungal total catch of the dust samples collected from the air conditioning system filters in I.C.U. and O.R. were ranged from 65.5-170 colonies/mg dust. Since, the interest to replace synthetic xenobiotics by natural compounds with low environmental persistence and biodegradable to control such airborne fungal contaminants is needed. In this respect, essential oils showed to possess a broad spectrum of antifungal activity. Fungal static ability of six oils was tested on 30 different fungal isolates. Vapors of common thyme oil exhibited the strongest inhibitory effects on the tested isolates, whereas the headspace vapors of blue gum and ginger had no inhibitory effects on the tested fungal isolates. These data revealed that the air conditioning systems may be an important source of contamination in I.C.U. and O.R. of Assiut university hospitals. Thus, patients may be in risk of being exposed to contaminated atmospheric air by opportunistic fungi and the use of essential oils as an alternative option to control hospital wards from fungal contaminants needs further studies. Key words: Air conditions, airborne fungi, intensive care units, operation rooms and volatile oils.

1. Introduction

Recently, increased attention has been paid to fungal

infections causing mycosis especially aspergillosis and

therefore microorganisms in hospital rooms were the

subject of many studies as the most important source of

fungal infections [1-3]. Most of these studies were

performed in intensive care units, surgical units, and

other departments where the risk of infections is great

[3-6]. Aspergillus, Fusarium and Mucor species were

found to be the most common fungal genera that

contaminate hospitals with low quantities ranging from

2 CFU/m3 to 26 CFU/m3 [7-10]. Indeed, fungal

Corresponding author: M. Bassam Aboul-Nasr, Ph.D.,

associate professor, research field: microbiology. E-mail: mbassamaboulnasr@yahoo.com.

contamination of the hospital rooms may occur due to

the growth of fungi on the organic matter of building

materials. The spores emanating from these colonies

could be inhaled by immunosupressed patients and

caused local infections, prior to possible dissemination

[11]. Although air-conditioning systems are essential

to maintain a comfortable indoor environment but also

are often contaminated by microbes which their

discharge into the indoor environment with strong air

currents may cause fungal contamination of the air. A

relation between bronchial asthma and fungal

contamination by air conditioning systems was studied

[12, 13]. The levels of nosocomial pathogens in the air

of hospitals increased due to dirtiness of air ducts

without regular replacement [14] in addition to organic

DAVID PUBLISHING

D

Indoor Surveillance of Airborne Fungi Contaminating Intensive Care Units and Operation Rooms in Assiut University Hospitals, Egypt

21

materials such as food, flowers and fruits derived from

outdoor by visitors and the interior structures of the

hospital [15]. The environmental fungal contamination

in hospitals and the incidence of invasive aspergillosis

were demonstrated by Ref. [7] and more than 500 cases

of post operative aspergillosis in immunocompetent

individuals were reported by Ref. [16]. Aspergillus

fumigatus and A. flavus were the leading species of the

genus Aspergillus causing invasive aspergillosis [17].

Vonberg and Gastmeier [18] reviewed all cases of

invasive aspergillosis and reported that the fungus

could be able to cause disease in an environment

containing less than 1 CFU/m3 of air.

Essential oils showed to possess a broad spectrum of

antifungal activity [19]. The advantage of plant

essential oils is their bioactivity in their vapor phase

which makes them used as possible antifungal

fumigants [20-22].

As it is known, very limited studies of the airborne

fungi in Egyptian hospitals especially I.C.U. and O.R.

were performed. In this context, the aim of this study

was focused on examining the spectrum and the level

of fungi in the atmospheric air and the dust samples

collected from the filters of their air conditioning

system in Assiut university hospitals. Also, studying

the antifungal activity of some essential plant oils (Blue

gum, Clove, Common thyme, Ginger, Lupine and

Radish) on the most prevalent fungal isolates collected

was assessed.

2. Materials and Methods

2.1 Media Used

Four types of agar media were used for isolation of

fungi (Sabouraud dextrose, Czapek’s glucose,

Czapek’s glucose at pH 8.5, and Czapek’s cellulose

agar media) [23].

2.2 Determination of Airborne Fungi

Airborne fungi of 12 of each I.C.U. and O.R. in

Assiut university hospitals were determined for two

consecutive years started from June 2008 to May 2010

using Koch sedimentation method according to Polish

Standard PN 89/Z-04008/08. Air mycoflora was settled

directly on three plates of the four types of media per

month for five minutes exposure time (optimal time for

hunting a reasonable and countable number of colony

forming units) in I.C.U. and 30 min in O.R. Plates were

incubated at 25 ± 2 °C for 7-10 days. The fungal count

was calculated as CFU/m3 according to the equation

CFU/m3 = no. of colonies × 10,000/surface of the Petri

dish × time of exposure × 0.2 [24].

2.3 Determination of Mycoflora of Air-Conditioning Filter’s Dust

Dilution plate method [25-29] was used to determine

the mycoflora of dust samples collected from

air-conditioning filters of I.C.U. and O.R. on the four

types of media used. The plates were incubated on 25 ±

2 °C for 7-10 days and TFC (total fungal colonies)

were calculated.

2.4 Identification of Fungi

Fungal genera and species were identified on the basis

of both macroscopic and microscopic characteristics

identification keys of Refs. [25, 28, 30-38].

2.5 Essential Oils Assay

Six volatile plant oils were purchased from local

markets, blue gum (Eucalyptus globules Labill.), clove

(Syzygium aromaticum L. Merr & L.M. Perry),

common thyme (Thymus vulgaris L.), Ginger (Zingiber

albus L.), lupine (Lupinus albus L.) and radish

(Raphanus sativus L.) and screened for their bioactivity

on the most prevalent fungal isolates collected. Fifty

mL of Czapek’s glucose agar medium [23] was poured

into a sterile Petri dish and left to solidify and

inoculated by the tested fungal isolate in its center. A

sterile filter paper disc (≈ 2 cm) was loaded with 50 µL

of the tested volatile oil and placed on the center of the

upper side of the Petri dish. The Plate was sealed with

polyethylene film and incubated upside down at 25 ±

2 °C for 7 days and the diameter of the fungal growth

was measured in cm [39].

Indoor Surveillance of Airborne Fungi Contaminating Intensive Care Units and Operation Rooms in Assiut University Hospitals, Egypt

22

3. Results and Discussion

Results summarized in Tables 1 and 2 revealed that

a total of 45 species belonging to 23 genera of

filamentous fungi were isolated and identified from

atmospheric air and dust samples collected from air

conditioning systems in I.C.U. and O.R. of Assiut

university hospitals. There were no appreciable

differences in air mycobiota of either I.C.U. or those of

O.R. as well as those of the filter’s dust samples of their

air conditions. Taxa isolated were belonging to three

taxonomic groups: Ascomycetes, Hyphomycetes and

Zygmycetes. The first group was represented by only

one species (Eurotium amstelodami), whereas the

second group comprised the greatest number of fungal

genera and species (39 species of 17 genera) and

Zygomycetes embraced five genera and five species.

The airborne total fungal forming units/m3 load in

I.C.U. and O.R. were ranged from 31.13-49.61

units/m3, whereas their total fungal catch in the dust

samples collected was ranged from 65.5-170

colony/mg. In one year study of fungal air

contamination in outdoor and inside two hematological

units in France, Sautuor et al. [40] found that the mean

viable fungal load was 122.1 CFU/m3 in outdoor

samples and 4.1 CFU/m3 in the units. More or less

similar results were reported by Ekhaise et al. [41].

They found that the fungal population in the air of five

different hospital wards was ranging from 10-53

CFU/m3. Falvey and Streifel [42] reported that the

mean recovery of the outdoor air was ranged from

22-122 CFU/m3, whereas the patient care areas in the

hospitals in Minnesota university hospitals comprised

the half number of the outdoor samples.

Although Aspergillus (17 species) and Penicillium

(five species) showed the greatest spectrum of airborne

fungi and dust samples of air conditions on all types of

media used, but Cladosporium (two species) was

recorded as the most common airborne genus

(19.35-32.8 CFU/m3 and frequently appeared in 100%)

followed by Aspergillus (0.97-19.93 CFU/m3 and

67%-100%) and fusarium came third (0.12-1.71

CFU/m3 and 17%-63%). Penicillium and Rhizopus

were collected with moderate to rare frequencies in

I.C.U.. However, Pencillium replaced Fusaium rank in

O.R. on all of the media used. Most likely, these results

came in agreement with those of Sautour et al. [40]

who isolated Fusarium with low frequency while Faure

et al. [8] isolated Cladosporium with 16% of total fungi

in the haematologic hospital in France.

In the present work, the total fungal catch units/mg

dust samples Aspergillus was the most dominant genus

where its total fungal count and frequency level of

appearance ranged between (43.5-147 colony/mg dust

and 100% respectively) followed by Fusarium (two

species), whereas Penicillum occupied the third place

in both I.C.U. and O.R.. All of these fungal genera

were similarly recorded by Refs. [5, 8, 43-45].

Table 1 Total fungal forming units (CFU/m3) and frequency levels (F%) of fungal genera and species of airborne fungi recovered on A-Czapek’s glucose, B-Czapek’s glucose at pH 8.5, C-Sabouraud dextrose, D-Cellulose agar media in 12 of each I.C.U. & O.R. at Assiut university hospitals.

D C B A Media used

O.R. I.C.U. O.R. I.C.U. O.R. I.C.U. O.R. I.C.U. Parameters Fungal species F% CFU F% CFU F% CFU F% CFU F% CFU F% CFU F% CFU F% CFU

4 0.03 Absidia corymbifera

8 0.06 8 0.0625 0.29 13 0.09 17 0.18 Acremonium strictum

25 0.2758 3.42 21 0.21 21 0.4417 0.1538 0.47 25 0.21 38 0.58 Alternaria alternate

88 6.3388 8.73 88 2.22100 19.9388 3.3667 1.83100 5.37 67 0.97 Aspergillus spp.

42 1.564 0.03 4 0.03 4 0.0342 0.57 13 0.09 A. aculeatus

4 0.038 0.11 13 0.15 54 8.7721 0.2725 0.47100 0.81 17 0.22 A. awamori

79 2.524 0.03 38 0.48 4 0.0338 0.45 8 0.18 A. candidus

13 0.09 13 0.09 A. flavipes

Indoor Surveillance of Airborne Fungi Contaminating Intensive Care Units and Operation Rooms in Assiut University Hospitals, Egypt

23

(Table 1 continued)

D C B A Media used

O.R. I.C.U. O.R. I.C.U. O.R. I.C.U. O.R. I.C.U. Parameters Fungal species F% CFU F% CFU F% CFU F% CFU F% CFU F% CFU F% CFU F% CFU

21 0.7263 4.51 33 0.3950 6.2933 0.3633 0.5879 0.93 21 0.33 A. flavus

17 0.2721 1.35 4 0.0313 0.228 0.06 4 0.06 4 0.03 A. fumigates

4 0.038 0.15 21 0.27 13 0.09 8 0.18 A. melleus

21 0.3 42 2.18 25 0.2129 2.8725 0.3617 0.5521 0.24 13 0.15 A. niger

38 0.784 0.03 4 0.038 0.064 0.03 4 0.03 4 0.03 A. niveus

4 0.0325 0.25 17 0.1533 0.738 0.098 0.0617 1.41 4 0.03 A. ochraceous

4 0.034 0.03 4 0.038 0.064 0.03 21 0.15 A. sulphureus

4 0.038 0.06 21 0.1817 0.1533 0.7813 0.1154 1.08 17 0.15 A. sydowii

4 0.03 A. tamarii

4 0.03 8 0.1225 0.6913 0.098 0.068 0.06 4 0.03 A. terreus

8 0.064 0.038 0.06 4 0.06 A. wentii

13 0.09 A. versicolor

4 0.03 4 0.03 Botryotricum piluliferum

8 0.064 0.03 13 0.33 Circinella muscae

100 27.84100 32.8 100 26.34100 19.35100 24.57100 25.06100 27.3 100 28.74 Cladosporium spp.

100 17.28100 19.71 100 18.36100 12.00100 17.67100 16.11100 20.01 100 18.37 C. cladosporioides

100 10.56100 13.09 100 7.98100 7.35100 6.9 100 8.95100 7.29 100 10.37 C. herbarum

4 0.0313 0.15 Cunninghamella echinulata

8 0.06 Curvularia lunata

13 0.0913 0.15 17 0.128 0.06 4 0.03 Drechslera spicifera

8 0.2913 0.068 0.06 13 0.15 Epicoccum nigrum

4 0.03 38 0.42 13 0.09 Eurotium amstelodami

63 0.9642 1.71 33 0.2438 0.6517 0.1229 0.2929 0.3 58 0.58 Fusarium spp.

50 0.5138 0.95 21 0.1817 0.36 13 0.1113 0.09 33 0.29 F. oxysporum

46 0.4538 0.76 8 0.0629 0.2917 0.1221 0.1813 0.21 33 0.29 F. solani

8 0.09 25 0.21 4 0.12 Mucor circinelloides

4 0.03 8 0.06 17 0.1817 0.06 13 0.15 Myrothecium roridum

58 1.7163 2.11 75 3.0654 2.5571 2.1333 0.5583 2.58 38 0.54 Penicillium spp.

29 0.3933 0.62 25 0.2442 0.6938 0.6 17 0.1525 0.21 17 0.15 P. chrysogenum

25 0.3 33 0.65 13 0.2421 0.2954 0.6913 0.1150 0.72 13 0.11 P. corylophilum

25 0.3325 0.51 33 0.3929 0.7338 0.3613 0.1171 1.08 13 0.11 P. duclauxii

33 0.4213 0.22 54 1.6525 0.4421 0.3 8 0.1546 0.51 13 0.11 P. italicum

17 0.274 0.11 33 0.5413 0.4025 0.184 0.034 0.06 8 0.06 P. oxalicum

17 0.1521 0.18 13 0.0942 0.3321 0.158 0.064 0.03 8 0.06 Rhizopus stolonifer

8 0.06 25 0.9 38 0.4529 0.4721 0.33 29 0.36 Scopulariopsis spp.

4 0.03 29 0.42 33 0.2725 0.2517 0.21 21 0.18 S.brevicaulis

4 0.03 21 0.48 17 0.1825 0.224 0.12 21 0.18 S. brumptii

13 0.15 17 0.15 38 0.33 21 0.18 Stachybotrys elegans

8 0.064 0.06 38 0.9817 0.1250 1.42 63 1.82 Stemphylium vesicarium

8 0.06 Talaromyces luteus

4 0.06 13 0.11 8 0.06 17 2.29 Ulocladium atrum

13 0.09 4 0.03 Verticillum albo-atrum

37.65 49.61 33.9 44.9 31.35 31.13 36.84 36.48 Total CFU

12 14 12 13 11 14 13 15 Number of genera (23)

30 30 32 30 32 26 33 29 Number of species (45)

Indoor Surveillance of Airborne Fungi Contaminating Intensive Care Units and Operation Rooms in Assiut University Hospitals, Egypt

24

Table 2 Total fungal catch (TFC/mg dust) and frequency levels (F%) of fungal genera and species of air conditioning filter’s dust samples recovered on A-Czapek’s glucose, B-Czapek’s glucose at pH 8.5, C-Sabouraud dextrose and D-Cellulose agar media, in 8 of each ICU and OR at Assiut university hospitals.

D C BA Media used

O.R. I.C.U. O.R. I.C.U. O.R. I.C.U. O.R. I.C.U. Parameters Fungal species F% TFC F% TFC F% TFC F% TFC F% TFC F% TFC F% TFC F% TFC

13 0.5 Alternaria alternate

100 43.5 100 77.5 100 53.5 100 85.5 100 88.5 100 147 100 104.5 100 114.5 Aspergillus spp.

38 18 50 28.5 75 28 75 45 50 47 88 123 88 77.5 88 96 A. awamori

75 16 63 7 75 23.5 88 16 75 24.5 50 19 63 18.5 63 14 A. flavus

13 0.5 50 12 13 0.5 25 2.5 25 15 13 1 0.5 13 0.5 A. fumigates

13 4 63 29.5 13 1 63 20 13 1 13 0.5 13 1 13 0.5 A. niger

38 5 13 0.5 13 0.5 25 2 38 1 13 3.5 13 1.5 25 1 A. ochraceous

25 1 A. tamari

25 1 13 0.5 A. terreus

13 0.5 A. ustus

13 0.5 A. versicolor

63 12 63 15 88 21 38 3.5 100 27.5 50 3.5 75 11 50 6.5 Fusarium spp.

38 3 38 3 75 7.5 13 1 88 10.5 12 0.5 75 3 25 2.5 F. oxysporum

63 9 50 12 88 13.5 38 2.5 100 17 50 3 63 8 50 4 F. solani

38 1.5 25 0.5 38 2 50 3 13 0.5 25 2.5 25 1 38 1.5 Mucor circinelloides

50 4 50 23.5 88 28.5 63 28 75 25.5 38 15.5 75 41 63 7 Penicillium spp.

38 3 38 3 50 8.5 50 3.5 50 10 25 4 75 5.5 38 1.5 P. chrysogenum

25 0.5 38 8 50 10 50 5 63 3.5 25 4.5 50 8 38 1.5 P. corylophilum

13 0.5 38 7.5 25 3.5 25 7.5 63 2.5 38 3 50 10.5 25 1.5 P. duclauxii

13 1 25 5 38 6.5 38 12 50 9.5 13 4 38 17 38 2.5 P. italicum

50 4 13 2 25 1.5 50 3 38 1.5 50 1 38 1.5 13 3.5 Rhizopus stolonifer

13 0.5 38 2.5 13 0.5 25 1 13 0.5 13 1 Stachybotrys elegans

65.5 121 107 124 143.5 170 159.5 134 Total TFC

6 6 6 6 5 6 6 6 Number of genera (7)

14 14 14 14 13 14 15 18 Number of species (19)

Panagopoulou et al. [5] studied the environmental

fungal load of air surfaces and tap water in three

hospitals in different regions in Greece and found that

A. niger was the most prevalent fungal species in the air

of all hospitals followed by A. flavus and A. fumigates.

In contrast, Augustowska and Dutkiewicz [46] isolated

A. fumigates as a dominant species (77% of total fungal

isolates) in air of a hospital in Poland.

Most of these fungi isolated from air or dust samples

collected in this study may cause different kinds of

mycosis. Aspergillus fumigatus is a known hazardous

agent which may cause allergic alveolities, asthma,

pulmonary aspergillosis and mycotoxicoses [46].

Pegues et al. [47] reported systemic infection A.

fumigatus in patient was happened at eleven days after

liver transplantation in France. Also, they found that

lung aspergillosis caused by the same fungal species

was detected in two patients at an intensive care unit.

Penicillium species were reported occasionally to

cause human penicillosis, pulmonary infection and

fungemia [48, 49]. Moreover Fusarium was reported as

causative agents of superficial and systemic infections

in humans [50].

In the second part of the study, the antifungal activity

of six types of volatile plant oils (blue gum, clove,

common thymus, ginger, lupine and radish) was tested

on 30 selected isolates belonging to six fungal species

(five/each). The results in Table 3 reflected that

common thymus oil completely inhibited the growth of

all fungal isolates studied but clove oil inhibited only

Indoor Surveillance of Airborne Fungi Contaminating Intensive Care Units and Operation Rooms in Assiut University Hospitals, Egypt

25

Table 3 The effect of volatile plant oils on the mean diameter/cm of the colony growth of different fungal isolates tested.

Fungal species Plant oils A B C D E F G

Aspergillus flavus 7.2 4.2 4 4.6 3.6 4.8 -

Aspergillus fumigates 6.2 4 4.6 4.6 2.4 4.8 -

Aspergillus niger 7.4 5.4 5.4 4.8 4.2 3.4 -

Cladosporium cladosperioides 2 1 1 - - 1.8 -

Fusarium solani 4.4 3.2 2.4 3.2 3.25 - -

Stachybotrys elegans 2.6 1.8 1.8 1.75 - 2.6 -

A = Control, B = Blue gum, C = Ginger, D = Radish, E = Clove, F = Lupin, G = Common thyme.

the growth of C. cladosporioides and S. elegans.

Lupine and radish oils inhibitory action affected only

F. solani and C. cladosporioides respectively. On the

other hand, volatile oils of both blue gum and ginger

had a partially or no inhibitory effects on all of the

tested fungal isolates. Montes-Belmont and Carvajal

[51] and Lee et al. [52] found similar results with those

in this study. Moreover, the essential oil of thymus

inhibited the growth of various fungi involved in food

spoilage, mycotoxin producers, pathogenic and wood

decay fungi [53, 54]. In contrast, Mourad et al. [55]

found that thymus oil exhibited moderate activity

against wood rot fungi. These results supported the

concept that plant oils could be used as fungicidal

components.

4. Conclusions

Aspergillus, Cladosporium, Penicillium, Fusarium

and several other fungal genera were recorded in the air

of different I.C.U. and O.R. in addition to the dust

samples of their air conditions at Assiut university

hospitals. These fungi are harmless for healthy people,

but they may be dangerous for patients of risk groups,

including those who are treated in O.R. and I.C.U. even

if their total count will be less than 1 CFU/m3 of air.

Therefore, air monitoring is important in hospitals

particularly in O.R. and I.C.U.. And the routine

maintenance of air-conditioning systems should not be

ignored. On the other hand, thymus oil had the greatest

ability to inhibit the growth of all fungal isolates

studied but still the use of essential oils as an

alternative option to control airborne fungi that

contaminate hospital wards need further studies.

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Journal of Health Science 2 (2014) 28-40

Decomposition of Surface Electromyographic Signal

Using Hidden Markov Model

Angela Abreu Rosa de Sá1, Alcimar Barbosa Soares1, Adriano de Oliveira Andrade1 and Slawomir Nasuto2

1. Biomedical Engineering Laboratory, Electrical Engineering Faculty, Federal University of Uberlândia, Uberlândia, Minas Gerais

38408-100, Brazil

2. Cybernetics School, University of Reading, Berkshire RG6 6AH, United Kingdom

Received: September 29, 2013 / Accepted: November 01, 2013 / Published: January 31, 2014.

Abstract: The detection of physiological signals from the motor system (electromyographic signals) is being utilized in the practice clinic to guide the therapist in a more precise and accurate diagnosis of motor disorders. In this context, the process of decomposition of EMG (electromyographic) signals that includes the identification and classification of MUAP (Motor Unit Action Potential) of a EMG signal, is very important to help the therapist in the evaluation of motor disorders. The EMG decomposition is a complex task due to EMG features depend on the electrode type (needle or surface), its placement related to the muscle, the contraction level and the health of the Neuromuscular System. To date, the majority of researches on EMG decomposition utilize EMG signals acquired by needle electrodes, due to their advantages in processing this type of signal. However, relatively few researches have been conducted using surface EMG signals. Thus, this article aims to contribute to the clinical practice by presenting a technique that permit the decomposition of surface EMG signal via the use of Hidden Markov Models. This process is supported by the use of differential evolution and spectral clustering techniques. The developed system presented coherent results in: (1) identification of the number of Motor Units actives in the EMG signal; (2) presentation of the morphological patterns of MUAPs in the EMG signal; (3) identification of the firing sequence of the Motor Units. The model proposed in this work is an advance in the research area of decomposition of surface EMG signals. Key words: Decomposition of EMG signal, hidden markov models, differential evolution, spectral clustering.

1. Introduction

Talking, walking and writring are examples of some

actions taken by the neuromotor system of the human

body. The movement is orchestrated by the coordinated

action of peripheral regions, spinal cord, brainstem and

cerebral [1].

Detection and analysis of physiological signals from

the Neuromotor System have been present in several

studies, from basic science to clinical diagnostics [2, 3].

Electromyography is an analytical method for the study

of physiology, biomechanics and Neuromotor System

fundamentals of human body [4]. Understand the EMG

(electromyographic) signal implies understanding the

Corresponding author: Angela Abreu Rosa de Sá, Ph.D., professor, research field: biomedical engineering. E-mail: angela@eletrica.ufu.br.

functioning of muscles and how bioelectrical signals

are generated [3, 5].

The EMG signal is derived from the sum of several

MUAP (Motor Unit Action Potentials) from the muscle

fibers, leading to muscle contraction [1]. In this way, the

decomposition of the EMG signal results in the set of the

various MUAPs that make up the EMG signal [6, 7].

MUAPs information, such as morphology, duration,

rate of occurrence and trigger time, is very used to

diagnose neuromuscular disorders [8, 9]. And also, the

morphology of MUAPs contains information about

health and anatomy of muscle fibers [10].

Thus, the analysis of MUAPs helps the professional

to assess if there is any motor disorder and what is its

origin: (1) motor neuron axon injury (neuropathy); (2)

the injury or muscle fiber atrophy (myopathy) [11-14].

DAVID PUBLISHING

D

Decomposition of Surface Electromyographic Signal Using Hidden Markov Model

29

The MUAPs presenting a myopathic disorder generally

have short duration and low amplitude. And the

MUAPs which present high amplitudes have

characteristic of neuropathic disorders.

Nevertheless, understand normal or abnormal

behavior control of Motor Units is essential in the

decision of the need of a pharmacological or surgical

intervention. And also, another important application

of EMG signal decomposition is in the area of ageing

and ergonomics, where it is interesting to understand

when the motor control is changed as a result of aging,

exercise, fatigue or excessive and prolonged power

production [15].

However, the process of EMG signal decomposition

is a complex task. The features of an EMG signal

depend on the type of electrode used (intramuscular or

surface), positioning relative to the muscle, the

contraction level and the clinical status of the

neuromuscular system of the patient [16].

In this context, some surveys have already been

initiated to study the decomposition of EMG signals

collected from surface electrodes, in order of the

disadvantages described earlier. However, despite the

interesting results already achieved, researches are

recent and are still in the early stage of development

[10]. So, there is a need for investigation of techniques

for decomposition of EMG signals collected from

surface electrodes, what would contribute to the

proposal for a new path for the research in the area of

surface electromyography.

Taking as inspiration the graphical probabilistic

models used in researches with surface

electroencephalographic signals in recent decades

[17-20], and considering the fruitful results presented

by the authors of those researches,

probabilistic-graphical models can be an interesting

technique to use with surface EMG signals. The use of

probabilistic-graphical models can be a new way to

implement a system of surface EMG signal

decomposition, able to make the classification of

MUAPs and calculate the probability of Motor Units

firing at a given time. With a tool that uses probabilistic

models for classifying MUAPs, it will be possible to

perform the estimation of the firing sequence of Motor

Units that composes the EMG signal. A technique with

this feature is very important as a help in evaluating the

operating mechanism of the neuromuscular system and

much needed for the biofeedback therapies focusing on

muscular rehabilitation.

Thus, the purpose of this work is to use the

probabilistic graphical hidden markov model, in the

process of decomposition of a surface EMG signal.

2. Materials and Methods

To develop the proposed system, initially it was

necessary to project a framework for the system to be

able to perform the EMG processing (noise elimination

and detection of MUAPs) and perform the

decomposition of surface EMG signal.

For the pre-processing step of EMG signal, that

includes the application of filter for elimination of

possible noise and MUAPs detection, the EMG

decomposition system BR was used [8]. Thus, this

system already provides the MUAPs present in EMG

signal. Then, it was used the Hidden Markov Model for

the MUAP clustering according to the morphological

similarity between them. And so, whereas a Motor Unit

generates a unique morphological pattern of MUAP, it is

possible to determine how many Motor Units are active

in EMG signal and also to present the morphological

pattern of the MUAPs generated by them.

Fig. 1 presents the diagram with the system structure

of surface EMG signal decomposition that was

developed, containing the whole process and the

techniques that were used in the decomposition of the

EMG signal, as well the responses that are presented by

the system.

2.1 MUAP Clustering

After the MUAPs detection stage, the next step

developed by the proposed system is the MUAP

clustering. This stage has the following functions:

Decomposition of Surface Electromyographic Signal Using Hidden Markov Model

30

Fig. 1 Block diagram of the structure of proposed system.

(1) Clustering of MUAPs that exhibit similar

characteristics in its morphology;

(2) Identify the amount of active Motor Units in

EMG signal that is being analyzed;

(3) Present the standard MUAP morphology that is

generated by each active Motor Unit,

To this end, the process of MUAP clustering is

accomplished by executing the following sequence:

(1) Feature extraction of MUAPs

In this step, selected features of MUAPs were

detected in EMG signal. The process of extracting

features of MUAPs was inspired by the work of the

researchers Kanar et al. [21, 22]. They developed an

algorithm based on Hidden Markov Model for pattern

recognition. The main difference between the classical

algorithms for pattern recognition and Hidden Markov

Models is the process of extracting features. In the case

of Hidden Markov Models, a uni-dimensional data can

be divided into a sequence of segments, and from this

sequence is extracted a vector of characteristics.

On the problem of recognition of dynamic behavior

studied by the researchers [21], a dynamic signal was

represented by a sequence y(k), k = 1, 2, ..., K, where K

is the amount of points. The procedure of feature

extraction is started with the division of the sequence

y(k) in T segments with L of length. Each segment is

represented by yt(l) (Eq. (1)).

yt(l) = y[(t-1)L+1] (1)

where, l = 1, 2, ..., L and t = 1, 2, …, T.

The next step is the extraction of characteristics of

each segment. The dynamic patterns in general are

characterized by successive segments increasing and

decreasing. Thus, the information of angulation and

curvature of each segment are components of the

Decomposition of Surface Electromyographic Signal Using Hidden Markov Model

31

vector of characteristics. These characteristics can be

obtained through polynomial approximations on each

segment. The angulation of the first-order polynomial

provides information about the behavior, that is,

increasing, decreasing or constant. And the

second-order polynomial can be used to get the second

derivative, which will provide information about the

curvature of the segment. And the third information

that will compose the vector of characteristics is the

average of the segment.

Thus, the vector of characteristics of each segment

will consist of:

Angle

The first-order polynomial approximate to the

sequence of points in a segment, can be expressed as

Eq. (2): (2)

where, t= 1, 2, ..., T and x is a continuous variable.

Curvature

The second order polynomial is defined according to

Eq. (3): (3)

The equation can be used to compute the second

derivative (Eq. (4)):

/ /

(4)

For this feature, the curvature is calculated at the

midpoint of the segment . Thus, the second feature

will be .

Average

The average of the points of the segment also provides

important information regarding signal level (Eq. (5)):

∑

(5)

Thus, for each segment t, where t = 1, 2, ..., T, the

authors will have a vector of characteristics ,

according to Eq. (6):

(6)

Then, in accordance with Kanar et al. [21], a

dynamic signal can be segmented into L segments and

each segment can be represented by a vector of

characteristics O (Eq. (7)):

, , , … , (7)

MUAPs features extraction using the method of

Kanar et al.

Whereas a MUAP morphology is similar to a

dynamic signal, that is, can be represented by a

sequence of increasing segments, decreasing or

constant, it is possible to apply the set of features

proposed by Kanar et al. [21], in the process of

extracting features of MUAPs.

Thus, a Motor Unit Action Potential can be divided

in L segments, and each segment will have a set of

features Ot (Fig. 2). After the stage of feature extraction

of MUAPs, the next step is to generate the Hidden

Markov Model, as shown below.

(2) Hidden Markov Model

The next step is to generate a Hidden Markov Model

that represents each MUAP detected in EMG signal.

The aim of creating a template for each MUAP is

explained by the need to build a Matrix of Similarity

between MUAPs patterns that is necessary for the

application of spectral clustering algorithm.

According to Kanar et al. [21], each set of features

extracted from a determined data can be considered as

being the observation that is observed in a state S. So, if

considering each segment and defining in the previous

section as a state, there will be a total of T states (Si).

And also, the transition of these states is always from

Fig. 2 Example of a MUAP represented by left-right topology of a Hidden Markov Model with T states, and each state S represents a segment t.

Decomposition of Surface Electromyographic Signal Using Hidden Markov Model

32

left to right, considering the dynamics of the evolution

of the EMG signal in time. Thus, the MUAP can be

represented by a Hidden Markov Model of T states,

with the left-right topology.

Thus, each MUAP detected on EMG signal, will be

extracted a set of features Ot, t = 1, 2, ..., T, where T is

the amount of segments of the MUAP. After performed

this step, it will be created a Hidden Markov Model,

left-right topology, with T states. Thus, each MUAP

will be represented by a H λ (Fig. 2).

For this topology of Hidden Markov Model, the state

transition matrix (A), will be represented by Eq. (8):

0 1 0 0 00 0 1 0 0

00 0 1 00 … 0 0 1

(8)

Each MUAP i that is presented in the EMG signal,

was created a Hidden Markov Model λi, using the set of

features Oi. Thus, the maximum likelihood produced

by model λi is that generated by the set of observations

Oi. It is important to highlight the fact that observations

with close values will necessarily, generate likelihood

with close values. And this case will happen when there

are MUAPs with similar morphologies. And, MUAPs

with similar morphologies will generate observations

with nearby values. Consequently, the likelihoods will

have close values. And also, considering that, these

will be happened generally:

A Motor Unit produces a single morphological

pattern of MUAP;

Different Motor Units generate distinct

morphological patterns of MUAPs.

Then it can be concluded that if generating a Matrix

of distance/dissimilarity between all MUAPs i and

using the likelihood generated by | , it is

possible to find out what are the MUAPs that have

similar morphologies, that is, what are the MUAPs that

were generated by the same Motor Unit. In this way,

how many distinct morphological patterns exist in the

EMG signal will be found, and therefore, the amount of

Motor Unit active in the EMG signal can be inferred.

Thus, in possession of the models λi and the set of

observations Oi, it is possible to construct a

dissimilarity matrix required to perform spectral

clustering algorithm.

(3) Spectral clustering

After the construction of the Hidden Markov Model

for each one of MUAPs present in EMG signal and

with the models λi and the set of observations Oi, the

generation of the Dissimilarity Matrix is as follows:

the cell (i, j) in the Distance Matrix corresponds to

| , that is, corresponds to the likelihoods of

the observations sequences , generated by the .

Thus, the Distance Matrix will be generated as

Eq. (9):

| | || | … |

…| | |

(9)

With the distance matrix, the spectral clustering

algorithm will be executed. As a result, the following

amounts will be obtained:

The amount of existing groups:

The spectral clustering algorithm will provide the

amount of existing groups between N likelihoods

provided in the matrix of distances. As a consequence,

the following amounts will be inferred:

The amount of morphological patterns of MUAPs;

The amount of active Motor Units in EMG signal.

The classification of each set of observations in a

given group:

After estimating the amount of groups, the spectral

clustering algorithm sorts each likelihood, through the

information was provided by the matrix of distance, in

one of the groups estimated. So, considering that each

group represents, in the work, an active Motor Unit, the

author will have as a result:

How many MUAPs were generated by each Motor

Unit;

What are the MUAPs generated by each Motor Unit;

What is the standard MUAP morphology generated

by each Motor Unit.

Decomposition of Surface Electromyographic Signal Using Hidden Markov Model

33

3. Results

To validate the methodology and the results of the

system, two data types are used: real and synthetic

EMG signals.

(1) Synthetic EMG signals

For the validation process of the proposed system, it

was used a synthetic EMG Signal Generator,

developed by Ref. [8]. In this simulator, to generate the

EMG signal, the inter-pulses characteristics of MUAPs

resulting from investigations of the first dorsal

interosseous muscle are considered.

This simulator of EMG signals allows the user to

simulate the hardware and generate synthetic EMG

signals according to the configuration of the following

parameters: (1) number of active Motor Units; (2) the

EMG signal simulation time in milliseconds; (3)

sampling frequency; (4) signal-to-noise ratio.

The advantage of using this simulator is due to the

fact that it is possible to evaluate the output of the

developed system, by using EMG signals with known

characteristics (the number of active Motor Units and

its firing sequence).

(2) Real EMG signals

The database of real EMG signals that was used for

the validation of the proposed project was provided by

Ref. [8]. The data were collected from 15 volunteers

who have run six different types of muscular contraction.

In total, 900 s is stored in this database EMG signal.

Signals were obtained through experimental data,

sampled at 10 kHz and collected using reference

electrodes (TECA NCS2000, Oxford Instrument

Medical, Ag/AgCl), array of surface electrodes

(MedTech Systems Ltd., Ag/AgCl) and invasive

electrodes (TECA X53153, Oxford Instruments

Medical) and needle electrode, which were placed in

first dorsal interosseous muscle of volunteers.

The advantage of using this database in the process

of validation of the proposed system is due to the use of

the array of electrodes. This array is composed of two

electrodes, differential double, and each one of them

has a catchment area of 1 mm in diameter and 3 mm

distant from the other electrode (centre to centre). In

this way, it has 2 surface electrodes close enough to

capture the same EMG signal and two EMG channels

storing these signals. Thus, the EMG signal picked up

by these two electrodes will be very similar due to the

proximity of the electrodes. This context is conducive

to the process of validation of the proposed system,

because it is possible to evaluate the system response in

the two channels and check the consistency between

the results provided.

3.1 Synthetic EMG Signals

The validation process using synthetic EMG signals

is presented in the following two tests with EMG

signals with different number of active Motor Units.

3.1.1 Test 1

For this validation test, it was raised a synthetic

EMG signal with the following characteristics: (1)

simulation time: 1,000 ms; (2) sampling frequency:

10,000 Hz; (3) number of Motor Units: 3; (4)

signal-to-noise ratio: 20 dB.

Fig. 3 presents the MUAPs detected by the software

EMG decomposition system. The dashed lines and

continuous indicate, respectively, the beginning and

end of each MUAP.

After the step of MUAPs detection, the next step is

accomplished by the proposed system: MUAPs

clustering.

The step of MUAPs clustering, using Hidden

Markov Model and Spectral Clustering, resulted in

three morphologically distinct groups of MUAPs (Fig.

4). This means that the system has detected 3 active

Motor Units in the EMG signal analyzed.

After the clustering stage, it is necessary to evaluate

the quality of the clusters detected. It is necessary to

evaluate the morphological cohesion between MUAPs

belonging to a same group.

For the evaluation of quality of MUAPs groups, the

algorithm to DE (differential evolution) has been used

[23]. This algorithm is designed to assess the quality of

the MUAPs groups held by Hidden Markov Model and

Decomposition of Surface Electromyographic Signal Using Hidden Markov Model

34

Fig. 3 MUAPs detected in synthetic EMG signal, delimited by the dashed lines and vertical solid.

Fig. 4 MUAPs groups detected in step of clustering: (a) group of MUAPs with standard waveform of type 1; (b) group of MUAPs with standard waveform of type 2; (c) group of MUAPs with standard waveform of type 3.

Spectral Clustering. In other words, the DE will check

if all MUAPs of a specific group really have the same

morphological pattern.

(1) MUAPs of Group 1

Fig. 5 presents the result of evaluating the quality of

MUAPs of Group 1, using the DE algorithm. After

Fig. 5 Quality evaluation of MUAPs of Group 1 using differential evolution algorithm.

running the DE, 100% of MUAPs converged to a

single morphological pattern, indicating that the

MUAPs of Group 1 is cohesive.

(2) MUAPs of Group 2

Fig. 6 presents the result of evaluating the quality of

MUAPs of Group 2, using the DE algorithm. After

running the DE, 100% of MUAPs converged to a

single morphological pattern, indicating that the

MUAPs of Group 2 is also cohesive.

(3) MUAPs of Group 3

Fig. 7 presents the result of evaluating the quality of

MUAPs of Group 3, using the DE algorithm. After

Decomposition of Surface Electromyographic Signal Using Hidden Markov Model

35

Fig. 6 Quality evaluation of MUAPs of Group 2 using differential evolution algorithm.

Fig. 7 Quality evaluation of MUAPs of Group 2 using differential evolution algorithm.

running the DE, 100% of MUAPs converged to a

single morphological pattern, indicating that the

MUAPs of Group 3 is also cohesive.

After the clustering stage, the authors have the

amount of Motor Units active in the EMG signal and

they also know the MUAPs that were generated by a

particular Motor Unit. That way, it is possible to return

to the EMG signal and determine the firing sequence of

Motor Units (Fig. 8).

Analyzing the correlation between firing sequence

of Motor Units of the synthetic EMG signal with that

generated through the proposed system, it was

evaluated the correlation between these sequences and

found to ρ = 0.99.

3.1.2 Test 2

For this validation test, there was raised a synthetic

EMG signal with the following characteristics: (a)

simulation time: 8,000 ms; (b) sampling frequency:

10,000 Hz; (c) number of Motor Units: 5; (d)

signal-to-noise ratio: 20 dB (Fig. 9).

Initially, it was held the MUAPs detection of the

EMG signal. After that, the step of MUAPs clustering,

using Hidden Markov Model and Spectral Clustering,

resulted in 5 groups of MUAPs, morphologically

distinct (Fig. 10).

In each one of the five groups of MUAPs, it was

found that DE algorithm was able to validate the

quality of the groups, it is, managed to detect only one

morphological pattern in each group. In groups 2 and 3,

DE achieved the convergence of 98% and 99% of the

population of MUAPs, respectively. In the remaining

groups, it was reached 100% of convergence with

MUAPs that belonged to a single pattern.

In this way, it is possible to infer that the Hidden

Markov Model and Spectral Clustering algorithm

reached a good quality in MUAPs clustering, as they

showed a strong similarity of pattern between the

members of all the groups analyzed.

And also, the system provided the firing sequence

of the Motor Units present in the EMG signal analysis.

To assess the correctness of this sequence, it was

calculated the correlation between it and the original

sequence that generated the synthetic signal, and was

obtained a correlation coefficient ρ = 0.98, which

indicates a high correlation between the two

sequences.

Decomposition of Surface Electromyographic Signal Using Hidden Markov Model

36

Fig. 8 Result of the proposed system: firing sequence of Motor Units.

Fig. 9 Synthetic EMG signal with five Motor Units actives.

3.2 Real EMG Signals

In the validation process with real EMG signals,

tests were conducted with the signals of the database

avaliable by Ref. [10], using the two channels collected

at array of electrodes.

For the validation of the results, the correlations of

system responses between the signals from the two

array of electrodes were observed. Table 1 presents a

summary of the application of the system in the EMG

signals collected from 15 volunteers. For each

volunteer, the following variables are presented:

(1) The amount of Motor Units detected in EMG

signal collected from the electrode 1;

(2) The amount of Motor Units detected in EMG

signal collected from the electrode 2;

(3) The correlation coefficient ρ between the firing

sequence of the Motor Units of the two EMG signals

collected by the two electrodes;

(4) The average correlation coefficient ρ between

morphological patterns of MUAPs detected between the

two EMG signals, collected by the two electrodes. This

average was calculated on the basis of the correlation

coefficient between all groups of morphological patterns

Decomposition of Surface Electromyographic Signal Using Hidden Markov Model

37

Fig. 10 MUAPs groups detected in step of clustering: (a) group of MUAPs with standard waveform of type 1; (b) group of MUAPs with standard waveform of type 2; (c) group of MUAPs with standard waveform of type 3; (d) group of MUAPs with standard waveform of type 4; (e) group of MUAPs with standard waveform of type 5.

of MUAPs detected in the two EMG signals.

The results obtained with the real EMG signals are

consistent with those that were expected for the

validation of the proposed system. The choice of this

database of EMG signals is due mostly to the fact of

having available signals collected by EMG electrodes

very close of each other (array of electrodes). This

setup was a necessary condition in order to validate the

Table 1 Summary of the application of the proposed system in the real EMG signals.

Volunteer

Motor Units Electrode 1

Motor Units Electrode 2

ρ sequences ρ MUAPS

1 2 2 0.88 0.91

2 3 3 0.92 0.89

3 3 3 0.89 0.91

4 2 2 0.90 0.75

5 3 3 0.93 0.79

6 2 2 0.86 0.87

7 2 2 0.92 0.96

8 3 3 0.88 0.93

9 3 3 0.88 0.91

10 2 2 0.82 0.77

11 2 2 0.88 0.91

12 3 3 0.90 0.94

13 2 2 0.70 0.84

14 4 4 0.71 0.83

15 3 3 0.88 0.94

proposed system for real EMG signals, because, due to

the proximity of the electrodes, the decomposition of

EMG signals detected by them should be consistent.

Thus, the consistency between the results obtained

from these two channels EMG, denotes the correctness

of developed system.

4. Discussion

In both types of tests conducted with synthetic and

real EMG signals, the system provided the following

results on the decomposition of surface EMG signal:

(1) Amount of actives Motor Units;

(2) Morphological pattern of the MUAP generated

by each Motor Unit;

(3) Firing sequence of the Motor Units.

In tests conducted with synthetic EMG signals, the

system has detected correctly the amount of active

Motor Units and presented, also, a strong correlation

between the firing sequence of Motor Units generated

by the proposed system and by the synthetic

signal-whose characteristics is already known.

The detection of the firing sequence of the Motor

Units was noted in Table 1, by examining the

correlation coefficient ρ, there was a strong correlation

Decomposition of Surface Electromyographic Signal Using Hidden Markov Model

38

between all Motor Units firing sequences analyzed.

This result demonstrates that the developed system

detected the correct sequence of firing of Motor Units,

because there was consistency in the correlation

between the two Motor Units firing sequences detected

by EMG signal collected by the two array of electrodes.

And also, in the analysis of synthetic signal, the system

showed a high correlation coefficient between the

firing sequence of the Motor Units detected by EMG

signal analysis and synthetic string that, that in fact

generated this signal EMG.

And also, when comparing the morphologic pattern

generated by the system for each EMG signal analyzed

of the array of electrode, the system also obtained a

strong correlation in all cases analyzed. To the two

electrodes, the system detected morphological patterns

of MUAPs similar, that is, detected the same amount of

active Motor Units and the same pattern of

morphological MUAP generated by each one of them.

In that way, it can be inferred that the system provided

answers consistent with those that were proposed.

It is important to note the use of DE algorithm for the

quality evaluation of a group of MUAPs and, also, in

the presentation of the morphological pattern of a

certain group of MUAPs: The final result of the

application of DE algorithm is exactly the

morphological pattern of the MUAP generated by the

Motor Unit. In all tests, it was obtained a convergence

of 100% of the MUAPs population for a single

morphological pattern, when considered the

neighborhood next to the pattern detected. This result

reflects very well the good functioning of the

probabilistic selection implemented in DE algorithm,

because it shows that the population, in no one of the

cases analyzed, became stuck in a great local and

prevented from reaching the great global.

It was possible to verify that the optimization of the

parameters of the Hidden Markov Model with DE

algorithm also proved to be effective, whereas in all

cases analyzed, HMM was raised so that the likelihood

between the HMM of MUAPs of EMG signal

presented the proximity necessary to be accomplished

the clustering, using the Spectral Algorithm, and thus

the amount of active Motor Units could be detected. If

HMM had not been raised correctly, this condition

would have been reflected in the clustering stage,

because it would not be possible to correctly identify

the amount of active Motor Units and the group

cohesion of MUAPs would not be detected

successfully when evaluated with DE.

Nevertheless, other existing systems of

decomposition of surface EMG signals use predefined

patterns of MUAPs to accomplish the grouping of

MUAPs and, thus, detect the amount of active Motor

Units. However, the proposed system does not need to

know a priori which is a pattern of MUAP, it will be

created a Hidden Markov Model for each MUAP

detected and, through the spectral clustering, they are

clustered in groups appropriate. Thus, the non-use of

predefined patterns of MUAPs is also a differential

technique implemented in this project.

The representation of each MUAP by a HMM, using

the technique of extraction of characteristics is a

scientific advance in the research area of

decomposition of surface EMG signal, since it is not

necessary to make the supervised clustering of MUAPs,

i.e., it is not necessary to know a priori the possible

MUAPs patterns that should be found in the EMG

signal.

It is therefore possible to conclude that the

probabilistic graphic Hidden Markov Model, spectral

clustering technique and the differential evolution have

potential applicability in the decomposition of surface

EMG signals. And also, these tools presented coherent

and cohesive results across all validation tests carried

out. Thus, this set of tools is promising and may be a

new direction for the research in the area of

decomposition of surface EMG signal.

5. Conclusions

Through the results obtained it is possible to infer that

the proposed system of decomposition of surface EMG

Decomposition of Surface Electromyographic Signal Using Hidden Markov Model

39

signal presented a functioning consistent with the

expected results. Thus, it is possible to affirm that the

developed system presented coherent results in terms of:

(1) Identification of the amount of active Motor

Units in EMG signal;

(2) Presentation of morphological patterns of

MUAPs presented in EMG signal;

(3) Identification of the firing sequence of Motor

Units in EMG signal.

It is important to emphasize the potentiality of the

Hidden Markov Model and Spectral Clustering for the

process of MUAP clustering of the surface EMG signal.

And also, the DE algorithm proved to be a good tool for

the process of internal quality assessment of MUAPs

groups. These tools presented in this article, which had

not been used in other researches in the area of

decomposition of EMG signals, provided excellent

results for surface EMG signal processing.

The developed system is not intended to solve all

problems concerning the decomposition of surface

EMG signals, but he presents a new approach and new

techniques which produce useful results to clinical

practice and Biofeedback therapies. The architecture of

the proposed model constitutes a breakthrough in the

research of decomposition of surface electromyography.

Despite the innovations of the techniques proposed

in the developed system and of the satisfactory results,

the proposed system has some limitations:

(1) The validation of the system was carried out only

for the First Interosseous Dorsal muscle I;

(2) The system does not treat the phenomenon

cross-talk and the superposition of MUAPs;

(3) The system does not consider the case of two or

more Motor Units generate the same morphological

pattern of MUAP, that is, it is considered that each

Motor Unit generates a morphological pattern of

MUAP distinguished;

(4) The system considers that a Motor Unit always

generates a same pattern of MUAP.

From the developed work, other studies may be

performed to improve the results and the application of

the proposed system:

(1) Investigation of the use of this system in

Biofeedback techniques;

(2) Validation, application and analysis of the

developed system in EMG signals from other muscle

groups;

(3) Investigation of the use of this system in clinical

practice;

(4) Calculating the probability of firing of Motor Units.

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Journal of Health Science 2 (2014) 41-55

Development of Commonsense Knowledge Modeling

System for Psychological Assessment in Clinical

Psycho

D.S. Kalana Mendis1, Asoka S. Karunananda2, Udaya Samaratunga3 and U. Rathnayake4

1. Department of Information Technology, Advanced Technological Institute, Dehiwala 10350, Sri Lanka

2. Faculty of Information Technology, University of Moratuwa, Moratuwa 10400, Sri Lanka

3. Gampaha Wickramarrachi Ayurveda Institute, University of Kelaniya, Kelaniya 11600, Sri Lanka

4. Department of Electrical & Computer Engineering, Open University of Sri Lanka, Nawala 10250, Sri Lanka

Received: October 15, 2013 / Accepted: November 26, 2013 / Published: January 31, 2014. Abstract: According to the Buddhist philosophy, hatred (dosa) is considered as one of the three unwholesome roots which determine the actual immoral quality of volitional states and a conscious thought with its mental factors. Hatred, then, comprises all degrees of repulsion from the faintest trace of ill-humour up to the highest pitch of hate and wrath. Thus, ill-will, evil intention, wickedness, corruption and malice are various expressions and degrees of dosa. A hateful temperament is said to be due to a predominance of the type of dosa, apo, vayu and semha. Vedic psychology forms the clinical core of mental health counseling in the Ayurvedic medical tradition. According to Ayurvedic medical practises, a person is dominated on one of constitutes type (type of dosa) namely vata (vayu), pita (apo) or kapha (semha). This is known as prakurthi pariksha. Important aspect of identification of constitute type is for diagnosis of mental diseases, because each of constituent type has a list of probable mental diseases. An important area of expertise for many clinical psychologists is psychological assessment. Constructions of information systems using psychological assessment in clinical psychology have a problem of effective communication because of implicit knowledge. This complicates the effective communication of clinical data to the psychologist. In this paper, it presents an approach to modeling commonsense knowledge in clinical psychology in Ayurvedic medicine. It gives three-phase an approach for modeling commonsense knowledge in psychological assessment which enables holistic approach for clinical psychology. Evaluation of the system has shown 77% accuracy. Key words: Human constituents, psychological assessment, clinical psychology, Ayurvedic medicine, commonsense knowledge modeling system.

1. Dosa

Dosa, which means malice, harted, ill-will, is one of

the three root-causes of unskillful or un-wholesome

actions (akusala-mula). It is consisted of greed (loba),

harted (dosa) and delusion (moha) as stated in Buddhist

philosophy [1]. But, whereas delusion is found in any

unwholesome deed or thoughts, greed and hatred stand

as two opposites, as attraction and repulsion,

respectively. Hatred, then, comprises of repulsion from

the faintest trace of ill-humor up to the highest pitch of

Corresponding author: D.S. Kalana Mendis, Ph.D., research

field: forensic psychiatry. E-mail: kalanaatil@mail.com.

hate and wrath. Thus, ill-will, evil intention,

wickedness, corruption and malice are but various

expression and degrees of dosa. Hate, of course, is

inspired by wrong views (miccha-ditthi), for, if things

are seen and understood in their proper perspectives, no

ill feeling can arise. Envy (issa), selfishness

(macchariya) and worry (kukkucaa) are always

associated with hatred or ill-will (dosa). Sometimes,

obduracy (thina) and sluggishness (middh) are closely

connected with certain forms of hatred [1].

A hateful temperament is said to be due to a

predominance of the elements cohesion (apo) and

DAVID PUBLISHING

D

Development of Commonsense knowledge Modeling System for Psychological Assessment in Clinical Psycho

42

oscillation (vayu) and also to a preponderance of

phlegm (semha) over the other humours in the body.

Hatred is paraphrased in Abhidhama terminology as a

disordred temper, getting upset, a feeling of disgust,

throwing off of a normal state and the abrupt reaction

of rage. It is annoyance (aghata) at the thought of harm

done to oneself or to someone dear or good done to a

person disliked. It may spring up as vexation due to

climatic conditions which prove a momentary obstacle,

such as the wind preventing one to dress. This would

lead to resentment (patighata) and repugnance

(patigha), and the latter is being more a passive state of

sense-reaction [1].

2. Ayurvedic Classification of Individuals

Ayurvedic medicine has a very strong bearing on the

concept of Prakurthi, which means nature (natural form)

of the build and constitution of the human body [2].

This has been evolved with Hatred (dosa), one of the

three unwholesome roots which determine the actual

immoral quality of volitional states and a conscious

thought with its mental factors [1, 3-9]. A hateful

temperament is said to be due to a predominance of the

type of dosa, apo, vayu and semha for diagnosing

mental diseases. According to Ayurveda, the path to

optimal health is different for people depending on

their Prakruti. For individuals, the Prakurthi is defined

as a combination of (vatha, pittha and kapha) [10]. A

balanced state of the Prakurthi makes a healthy and

balanced person (physically and mentally). Since the

authors all have different combinations of the Prakurthi.

The diagnosis of prakruti offers unique insights into

understanding and assessing one’s health. It is not

merely a diagnostic device but also a guide to action for

good health. It assesses the, dominance of Prakurthi

and gives advice for preventive and primitive health

care. The ancient science of Ayurveda is the oldest

known form of health care in the world. Important

aspect of identification of constitute type is for

diagnosis of mental diseases, because each of

constituent type has a list of probable mental diseases

[10-14] such as an important area of expertise for many

clinical psychologists which is psychological

assessment (Table 1).

3. Psychological Assessment in Clinical Psychology

Clinical psychology is an integration of science,

theory and clinical knowledge for the purpose of

understanding, preventing, and relieving

psychologically based distress or dysfunction and to

promote subjective well-being and personal

development. Central to its practice are psychological

assessment and psychotherapy, although clinical

psychologists also engage in research, teaching,

consultation, forensic testimony, and program

development and administration. In many countries,

clinical psychology is a regulated mental health

profession. Psychological Assessment is concerned

mainly with empirical research on measurement and

evaluation relevant to the broad field of clinical

psychology. The areas of assessment processes and

methods are included as given below [15]:

Clinical judgment and the application of

decision-making models;

Paradigms derived from basic psychological

research in cognition, personality-social psychology,

and biological psychology;

Development, validation, and application of

assessment instruments, observational methods, and

interviews.

4. Psychological Assessment in Clinical Psychology of Ayurvedic Medicine

Recognition of human constituent in Ayurveda, is

currently based on a standard questionnaire on

subjective criteria based on ancient theories of

Ayurvedic scholar Charaka, 1000 BC and Susruta,

600 BC [10] as a psychological assessment in clinical

Table 1 Classification of mental diseases.

vata pittha kapha

anxiety disorders anger disorders depression disorders

Development of Commonsense knowledge Modeling System for Psychological Assessment in Clinical Psycho

43

psychology. Classification of individuals through

clinical examination in Ayurveda has been considered

[16]. The clinical examination of Ayurveda is divided

into two paths, namely: examination through patient

and examination through disease. Prescribing drugs for

a disease is depended on both two examinations.

Classification of individual human constituents is

included in examination through patient, which defined

as a concept called “prakurti pariksha”. Individual can

be categorized into vata or pita or kapha based on the

“prakurti pariksha”. It was defined that one type can be

dominated but in combination of all 3 types. Chopra

Center [17] built a web base system to discover the type

of body constituent type. A questionnaire is used to

diagnose constituent type. This dosa centre also built a

web based system based on a questionnaire to predict

type of prakurthi [18, 19]. There was also a web system

to evaluate type of prakurthi based on a questionnaire

and predict percentage of relevant type of prakurthi

[20].

In exciting systems, the method of analyzing

constituents is not consistent. Questions in concerned

are very much user-friendly and based on medical

theories of Ayurveda, which is used for finding

constituent type and probes such as repeating questions

and classification of constituent type and its possible

mental diseases. Anxiety disorders are depended on

vata constituent type. This has been used for

classification of individuals for many centuries. There

is no research into improving the questionnaire

although people have realized that the classification is

not acceptable sometimes.

David Paul built an approach for collaborative

activities in virtual settings enabling the different

parties to achieve their desired objectives by examining

them from a knowledge management perspective in

tele medicine [21]. Dwivedi et al. could make

web-based multimedia patient administration systems

be the norm for healthcare institutions. Such a scenario

is likely to lead to a situation where healthcare

institutions would be flooded with large amounts of

clinical data. The introduction of the KM (knowledge

management) paradigm would enable healthcare

institutions to face the challenge of transforming large

amounts of medical data into relevant clinical

information. A KM solution would allow healthcare

institutions to give clinical data context, so as to allow

knowledge derivation for more effective clinical

diagnoses [22]. Kimble Chris presented a framework

for categorizing virtual teams and argued that

fundamental changes have taken place in the business

environment which force people and organizations to

operate in “two spaces” simultaneously: the physical

space and the electronic space. It highlighted some of

the issues of trust and identity that existed in virtual

teams and argued that, due to certain barriers, only a

small proportion of these teams reached a satisfactory

level of performance. Using the evidence from two

recent sets of studies, it highlighted some of the barriers

to effective virtual team working and demonstrateed

the critical importance of trust and social bonding to

the functioning of such teams. It reported on the use of

a “Community of Practice” in a virtual team and argued

that this may provide one mechanism for overcoming

some of the barriers [23]. Julie Parker and Enrico

reviewed improving clinical communication for a

cognitive psychological perspective, focusing on

current understandings of how human memory

functions and on the potential consequences of

interruptions on the ability to work effectively. It was

concludeed by discussing possible communication

technology interventions that could be introduced to

improve the clinical communication environment [24].

Richard Lenz elaborated both the potential and the

essential limitations of IT support for healthcare

processes. It has been identified different levels of

process support in healthcare, and distinguished

between organizational processes and the medical

treatment process. To recognize the limitations of IT

support, it has been adopted a broad socio-technical

perspective based on scientific literature and personal

experience [25]. Fallowfield discussed some of the

Development of Commonsense knowledge Modeling System for Psychological Assessment in Clinical Psycho

44

issues that influenced communication within an

oncology setting, and ultimately affect patient.

Oncologists themselves acknowledge that insufficient

training in communication and management skills is a

major factor contributing to their own stress, lack of job

satisfaction and emotional burnout. Consequently, over

the past few years there have been several initiatives

aimed at improving basic communication skills

training for healthcare professionals in the cancer field

[26]. Mario Stefanelli discussed the role of mobile

communication systems. Moreover, the paper

discussed the role of mobile communication and

speech understanding technologies to support a

satisfactory user-system interaction in daily work [27].

Using psychological assessment in clinical

psychology had a problem of effective communication

because of implicit knowledge for constructing

Information systems. This complicated the effective

communication of clinical data to the psychologist in

support of clinical psychology.

As such the authors decided to resolve the problem

with the help of AI (Artificial Intelligent) techniques.

An approach as Mark suggested has been explored in a

program called OPAL, which allows medical

specialists working alone to enter and review cancer

treatment plans for use by an expert system called

ONCOCIN. Knowledge-acquisition tools based on

strong domain models should be useful in application

areas whose structure is well understood and for which

there is a need for repetitive knowledge entry [28].

Ramoni, MT model accounted for all of the conceptual

features of knowledge-based systems, thus making

clear which features were intrinsic to the problem and

which were artifacts of the implementation. The

proposal was based on a two-level analysis of

knowledge-based systems: an epistemological and a

computational level [29]. James proposed that a

generalization of the set covering problem can be used

as an intuitively plausible model for diagnostic

problem solving. Such a model was potentially useful

as a basis for expert systems in that it provided a

solution to the difficult problem of multiple

simultaneous disorders [30]. John Protégé-2000, could

be run on a variety of platforms, supported customized

user-interface extensions, incorporates the OKBC

(Open Knowledge-Base Connectivity) knowledge

model, interacted with standard storage formats such as

relational databases, XML, and RDF. Using Protégé,

developers and domain experts could easily build

effective knowledge-based systems, and researchers

could explore ideas in a variety of knowledge-based

domains [31]. So it is well known fact that Expert

systems are better at solving real world problems,

which cannot be solved otherwise [32-38]. In particular

Expert systems can be used to models domains with

less formal knowledge [39-42].

5. Commonsence Knowledge Modeling System

In this paper an approach was presented to model

commonsense knowledge in psychological assessment

for clinical psychology in Ayurvedic medicine evolved

by dosa in Buddhist studies [43-45] using an Expert

system based on principal component analysis and

statistical fuzzy inference system. Dosa in Buddhist

studies stated that ill-will, evil intention, wickedness,

corruption and malice are various expressions and

degrees of dosa and hateful temperament is said to be

due to a predominance of the type of dosa, apo, vayu

and semha. This gives knowledge modeling approach

for modeling commonsense knowledge in,

psychological assessment which enables holistic

approach for clinical psychology to find:

Type of dosa (constituent type: vata, pitta, kapha)

in percentages;

Dominant type of dosa;

Possible metal disease based on type of dosa.

Principal component analysis is used for exploring

data to reduce the dimension. Generally, PCA

(principal component analysis) seeks to represent n

correlated random variables by a reduced set of

uncorrelated variables, which are obtained by

Development of Commonsense knowledge Modeling System for Psychological Assessment in Clinical Psycho

45

transformation of the original set onto an appropriate

subspace. The uncorrelated variables are chosen to be

good linear combination of the original variables, in

terms of explaining maximal variance, orthogonal

directions in the data. Two closely related techniques,

principal component analysis and factor analysis, are

used to reduce the dimensionality of multivariate data.

In these techniques correlations and interactions

among the variables are summarized in terms of a

small number of underlying factors. The methods

rapidly identify key variables or groups of variables

that control the system under study. The resulting

dimension reduction also permits graphical

representation of the data so that significant

relationships among observations or samples can be

identified.

Other techniques include multidimensional scaling,

cluster analysis, and correspondence analysis.

MDS (multidimensional scaling) is a set of related

statistical techniques often used in information

visualization for exploring similarities or

dissimilarities in data;

Cluster analysis or clustering is the assignment of

a set of observations into subsets (called clusters) so

that observations in the same cluster are similar in

some sense;

CA (correspondence analysis) is a multivariate

statistical technique proposed by Hirschfeld and later

developed by Jean-Paul Benzécri. It is conceptually

similar to principal component analysis, but applies to

categorical rather than continuous data. In a similar

manner to principal component analysis, it provides a

means of displaying or summarizing a set of data in

two-dimensional graphical form [46-48].

Inference is the act or process of deriving logical

conclusions from premises known or assumed to be

true. The conclusion drawn is also called an inference.

The laws of valid inference are studied in the field of

logic. Human inference (i.e., how humans draw

conclusions) is traditionally studied within the field of

cognitive psychology; artificial intelligence

researchers develop automated inference systems to

emulate human inference. AI systems first provided

automated logical inference and these were once

extremely popular research topics, leading to

industrial applications under the form of expert

systems and later business rule engines. Bayesian

inference has applications in artificial intelligence and

expert systems. Bayesian inference techniques have

been a fundamental part of computerized pattern

recognition techniques since the late 1950s. There is

also an ever growing connection between Bayesian

methods and simulation-based Monte Carlo

techniques since complex models cannot be processed

in closed form by a Bayesian analysis, while a

graphical model structure may allow for efficient

simulation algorithms like the Gibbs sampling and

other Metropolis-Hastings algorithm schemes.

Recently Bayesian inference has gained popularity

amongst the phylogenetics community for these

reasons; a number of applications allow many

demographic and evolutionary parameters to be

estimated simultaneously. In the areas of population

genetics and dynamical systems theory ABC

(approximate Bayesian computation) are also

becoming increasingly popular [49].

Bayesian inference is a method of statistical

inference in which evidence is used to estimate the

probability that a hypothesis is true. The term

“Bayesian” comes from the application of Bayes’

theorem to probabilities that specifically have the

interpretation as Bayesian probabilities. Such

probabilities can themselves be distinguished into

objective and subjective probabilities. In practical

usage, “Bayesian inference” refers to an iterative

process in which collection of fresh evidence

repeatedly modifies an initial confidence in the truth

of a hypothesis. In each iteration, the initial belief is

called the prior probability, whereas the modified

belief is called the posterior probability. Fuzzy logic is

an alternative to Bayesian inference. Fuzzy logic and

Bayesian inference, however, are mathematically and

Development of Commonsense knowledge Modeling System for Psychological Assessment in Clinical Psycho

46

semantically not compatible [50]. You cannot, in

general, understand the degree of truth in fuzzy logic

as probability and vice versa; fuzziness measures “the

degree to which an event occurs, not whether it

occurs” [49, 51].

Fuzzy logic and probability are different ways of

expressing uncertainty [52, 53]. While both fuzzy logic

and probability theory can be used to represent

subjective belief, fuzzy set theory uses the concept of

fuzzy set membership (i.e., how much a variable is in a

set), and probability theory uses the concept of

subjective probability (i.e., how probable do I think that

a variable is in a set). While this distinction is mostly

philosophical, the fuzzy-logic-derived possibility

measure is inherently different from the probability

measure, hence they are not directly equivalent. While

this distinction is mostly philosophical, the

fuzzy-logic-derived possibility measure is inherently

different from the probability measure, hence they are

not directly equivalent.

In the first place, the authors have tried statistical

technique of PC (principal component) analysis [54] for

recognition of any dependencies among classification

of individuals using the questionnaire as a

psychological assessment. Among other AI techniques,

the authors have used Fuzzy logic [55] to fine tune the

results obtained from PC analysis. Finally the system

has been developed as an Expert System [56], which

models Ayurvedic classification of individuals. With

this technology the system has added features such as

incorporating new knowledge, explaining reasons for

answers given.

6. Methods

The authors postulate a new approach enhancing the

ability of classifying human constituents using an expert

system based on principal component analysis and

Fuzzy logic. It has been extended from constructions of

membership functions [33, 45] to statically based

defuzzification process. This has been exploited the

process of the new approach in following steps.

6.1 Removing Dependencies

The approach begins by acquiring commonsense

knowledge. This can be done as an interview between

domain experts and the knowledge engineer. Using the

interviewing process between expert and knowledge

engineer, commonsense knowledge has been acquired

and mapped in to a questionnaire based on Likert scale

technology [57]. The authors have chosen to acquire

tacit knowledge into a questionnaire since it is more

convenient for further analysis. On the other hand, the

questionnaire can be automated to interact directly with

the domain expert without involving a knowledge

engineer. Once tacit knowledge has been acquired then

the knowledge for finding dependencies should be

analyzed. The questionnaire has been analyzed using

PC (principal component) analysis [54] to find

dependencies.

What is PC analysis?

The concept of PC analysis is based on the

derivation of linear combinations of the p measured

variables X1, X2, …Xp to produce “derived variables”,

that are uncorrelated and are such that explains a

different “dimension” within the data [54]. Such

derived variables are referred to as PCs (principal

components). As there are p response variables within

the data set, p principal components can be derived.

The first PC, denoted PC1, is expressed in the form

pp XXXPC 12121111 .... (1)

where, the terms refers to the weight of each

variable within this principal component PC1. The

weights of each PCi represent the eigenvector solution,

which maximize the variance of each PCi, where i is the

number of components [35].

Extracting principal components

The importance of each PC, in terms of level of data

variation explained, is specified by its eigenvalue, the λ

term, with Σ λ representing the total of the p eigen

values. A measure of the proportion of data variation

accounted for by each PC, based on the equivalence of

eigenvalue and PC variance, is provided by the

expression λ/(Σ λ).

Development of Commonsense knowledge Modeling System for Psychological Assessment in Clinical Psycho

47

Generally, it is required to select those PCs, which

account cumulatively for at least 80% to 90% of the

data variation. In addition, each PC must exceed

eigenvalue more than 1. However, if nearly all the

correlations are less than 0.25, there is probably no

purpose in carrying out a PCA. However, to reduce

even that much of interdependency PCs can be

computed.

PC for commonsense knowledge modeling

(model refinement)

Let S be the set of all questions in the questionnaire

and P be the set of all extracted principal components.

Further,

nn

rrpp

PCPC

PCPCPCPCPCPCP

,...

,...,,..,

1

1121

mmssqq SSSSSSSSS ,,...,,...,,.., 11121

mimmimsisssi

qiqqqiiii

SaSaSaSa

SaSaSaSaPC

,1,11,1

1,12211

......

...

(2) Let M be the principal components Matrix for

filtered commonsense knowledge.

mnmrmrmpmpmm

nrrpp

nrrpp

aaaaaaa

aaaaaaa

aaaaaaa

M

...,...

.

.

.........

...,......

1121

21221222221

11111111211

3

For n number of extracted principal components,

following computation is concluded.

n

jjPCX

1

(4

X

n

j

m

iiij Sa

1 1

5

X=i

n

rj

m

siiji

r

pj

s

qiij

p

j

q

iiij SaSaSa

1 11 11 1

(6)

Let LS be the Likert scale [11], then

ULLS ,.., (7)

XL and XU values are derived from results of the

filtered commonsense knowledge using principal

component analysis. It is computed as given below

UL XXX ...

UnLn

ULUL

XX

XXXXX

...

,.....,...,... 2211 (8)

n

ij

m

siijnLn aLX

1 1

(9)

n

ij

m

siijnUn aUX

1 1

(10)

6.2 Statistical Fuzzy Inference—(Fine Tuning)

This phase is constructed by integrating output of

model refinement with fuzzy inference system. It is

consisted with following stages:

Fuzzfication

In this sub phase of fuzzification, it basically

analysis the fuzzy set and membership function for

commonsense knowledge modeling. Membership

functions have been constructed by using output of

model refinement.

Let A be fuzzy set defined on a fuzzy concept using

the interval of

)...(),...,..(,... 2211 UnLnULUL XXXXXX

Membership functions are defined as follows:

For UnLnn XXL ...

UnLn

Lnn XX

XXXA )( (11)

Fuzzy rule base

Fuzzy rule base has been constructed by using the

membership functions defined in fuzzification process.

Fuzzy rules can be constructed as follows, Rule n. If X > XLn AND X < XUn

LnUn

Lnn XX

XXXA )( (12)

Adding dynamically, in order to operate the

reasoning process for answers given by the fuzzy rules,

it can extend further in to a fuzzy rule base.

Here nKKK ..., 21 are defined as singleton fuzzy

sets

Development of Commonsense knowledge Modeling System for Psychological Assessment in Clinical Psycho

48

)(

...)()(

2

2211

UUn

LULU

LnUnn

XX

XXXX

XXK

(13)

Defuzzification

The input for the defuzzification process is a fuzzy

set (the aggregate output fuzzy set) and the output is a

single number. As much as fuzziness helps the rule

evaluation during the intermediate steps, the final

desired output for each variable is generally a single

number. However, the aggregate of a fuzzy set

encompasses a range of output values, and so must be

defuzzified in order to resolve a single output value

from the set. Defuzzification has been implemented

using Sugeno-Type Fuzzy Inference [58].

Here K1, K2, …, Kn are defined as singleton fuzzy

sets.

Rule n. If

LnUn

Lnn XX

XXXA )(

nKZ (14)

Let Z be the output of rules defined in Sugeno-Type

fuzzy inference

)(...)()(

*)(...*)(*)(

21

2211

XAXAXA

KXAKXAKXAZ

n

nn

(15)

7. Framework for Commonsence Knowledge Modeling System

The framework for modelling of commonsense

knowledge has been developed on the basis of phases

mentioned above. Such the framework enables PC

analysis, knowledge classification and intelligent

reasoning using the expert system technology.

Functionally the entire system can be seen as a

fuzzy-expert system. Fig. 1 shows the top-level

architecture of the framework. It consists of a user

interface, inference engine, knowledge base, fuzzy

logic module, principal component analyzer and a

database.

Commonsense knowledge has been extracted from

the expert and formulated in a questionnaire. It is

evaluated using Likert scale technology. In the first

Fig. 1 Top level architecture of system.

instance of knowledge acquisition, a pilot survey has

been done for the purpose of extracting principal

components. The SPSS is used for conducting the

functions of principal components extracting.

7.1 Fuzzy Logic Module

The output results of the principal component

analyzer would be the input for the fuzzy logic module.

In the case of generating membership function, finding

the interval is considered as an automated process in

this module due to instead of using runtime inputs. This

module has been implemented using Visual Basic for

widening scope of generating membership function.

Further, fuzzy rules have been constructed in the fuzzy

logic module.

7.2 Database

Extracted principal components have been stored in

Ms Access database, which integrated with the

principal component analyzer through the developer

interface that is considered as a sub interface of the user

interface. The questionnaire consisted of tacit

knowledge also has been stored in the database that

integrated with the user interface.

7.3 Knowledge Base

Explanations for output generated by the fuzzy logic

module have been processed using fuzzy rules in the

Development of Commonsense knowledge Modeling System for Psychological Assessment in Clinical Psycho

49

knowledge base. Further, knowledge engineer is given

a facility to add new rules in the runtime. The

knowledge base has been implemented using FLEX

expert system shell, which embedded in Win-Prolog.

7.4 User Interface

The user interface facilitates for both developer and

general user. Once knowledge engineer develops a

particular framework for required tacit domain with

interaction of the expert, and then general user will be

given a facility of using the framework for

decision-making purposes. So, it has been divided the

user interface in developer interface and general user

interface. General user will be able to use a developed

framework using a questionnaire, which has been

implemented as a web page linked to the database.

7.5 Inference Engine

The inference engine carries out the reasoning

whereby the expert system reaches a solution. This is

the inference engine of the FLEX expert system shell.

Since this is built in to the system, there is no

development activity with regard to this component in

the system. Note that inference engine has nothing to

do with the modeling of commonsense knowledge but

it runs the expert system.

8. System in Practice

In the exciting system, the method of analyzing

constituents is not consistent. Although Ayurvedic

practitioners use a psychological questionnaire, it leads

to several problems like dependencies among the

questions in the questionnaire and analysis of the

constituent type. These problems were addressed to

solve using following stages.

8.1 Extracting Commonsense Knowledge in Ayurveda

In the first instance, the authors mapped

commonsense knowledge regarding to analysis of

constituents to a (psychological assessment)

questionnaire with interaction of an Ayurvedic expert.

It is consisted of 72 questions to analyze vata, pita and

kapha. It is certainly need to measure attitudes during

the practical communication work. The questionnaire

can be produced very rapidly on Access database

(Table 2):

8.2 Removing Dependencies

The authors have done a pilot survey using 100 No.

of students for statistical modeling. Principal

component analyzer has been used to remove

dependencies. It has been identified 25 principal

components using SPSS [59] as shown below in a

matrix form (Fig. 2). Here V1, V2, V24, K1, K2, …,

K24, P1, P2, …, P24 denote question-numbering

system in the questionnaire.

Human constituents can be computed in to vata, pita

and kapha in percentages as shown in Fig. 3.

Membership functions for vata, pita and kapha have

been constructed using the out puts of principal

component analyzer.

For example, Membership function for Vata

constitution

Table 2 A part of 72 numbers of questions in the questionnaire.

ID Question Marks-range Marks

1 My skin is cracked, dry and cold 1-6

2On my skin, vains and tendons are easily visible

1-6

3 I am tend to be slight sweating 1-6

4 I have less body smell 1-6

5 Under developed body build 1-6

6 I do not gain weight very easily 1-6

Respondents are required to enter their answers directly at the computer.

1 2 .. 24 25V1 -0.228622 0.249362 . -0.073945 0.058179V2 0.08431 0.20654 . -0.097192 -0.112795. V=.V23 -0.645803 0.232312 . 0.0067 -0.083959V24 -0.222147 -0.06453 . -0.073514 0.084404K1 0.012511 -0.096332 . 0.141314 0.25113K2 -0.005642 0.268145 . -0.179992 0.111715. K=

M = .K23 0.409442 0.073812 . -0.115118 -0.056431K24 0.696973 0.126679 . 0.098213 0.045471P1 0.430044 0.14608 . 0.023669 0.09045P2 0.243781 0.373485 . -0.040468 0.149644.. P=P23 0.009727 0.012529 . -0.072224 0.177827P24 -0.378091 0.096985 . 0.158006 0.069821

Fig. 2 Principal components identified in the system.

Development of Commonsense knowledge Modeling System for Psychological Assessment in Clinical Psycho

50

 

Fig. 3 Analysis of human constituents.

For 111 ... UL XXL (16)

1LX

25

1

24

1

510004.8i j

jia (17)

6UX

25

1

24

1

06002.51i j

jia (18)

8.510004 51.06002

8.510004)(1

XXA (19)

8.3 Fuzzy Rule Base

Fuzzy rules have been constructed for classification

of each of constituent’s type.

For example, Vata constitution

Rule 1. If X > 8.510004 and X < 51.06002

8.510004 51.06002

8.510004)(1

XXA (20)

Defuzzification

Defuzzification process has been computed using

Sugne–style inference technique:

Here 321 ,, KKK are defined as singleton fuzzy

sets.

For example, vata constitution

K1 = 42.550016/(55.5856 + 107.53602 + 42.550016)

= 20.68833.

For example, vata constitution

Rule 1. If

8.510004 51.06002

8.510004)(1

XXA (22)

then K1 = 20.68833.

This computation will defuzzify the output of

defuzzification process as 25.08375.

Further K1, K2, K3 are defined as singleton fuzzy sets.

For vata constitution,

K1 = 42.550016/(55.5856 + 107.53602 + 42.550016)

= 20.68833.

For pitta constitution,

K2 = 107.53602/(55.5856 + 107.53602 + 42.550016)

= 27.02638.

For kapha constitution,

K3 = 55.5856/(55.5856 + 107.53602 + 42.550016) =

52.2853.

100*)()()(

*)(.*)(*)(

321

233211

XAXAXA

KXAKXAKXAZ

(23)

Z = out put =25.08375.

So body constitution is concluded as value between

vata and pitta.

By clicking explanation button in Fig. 3, it will show

an output analysis and window (Fig. 4) of completed

evaluation. This has been implemented using FLEX

expert system shell [60].

This evaluation is consisted with:

- Vata, kapha, pita are in a combination (%);

- Determination of dominated constituent type.

8.4 Explanations for Derived Human Constituents

Explanations for output generated by the fuzzy logic

module have been processed using fuzzy rules in the

knowledge base in the expert system. The knowledge

base has been implemented using FLEX expert system

shell, which embedded in Win-Prolog. In relation to

Ayurvedic domain, possible mental diseases can be

occurred due to dominated constituent type (dosa). It is

illustrated as shown in Fig. 4.

9. Analysis of Results

The authors set up their evaluation criterion as a

comparison between the system and a real world expert

in the similar domain. Both Ayurvedic expert and the

system have been used to investigate human

constitutions separately.

Development of Commonsense knowledge Modeling System for Psychological Assessment in Clinical Psycho

51

Fig. 4 Analysis and reasoning window in Ayurvedic domain constructed using FLEX.

The layman-expert and layman-system have been set.

up into two groups. Here layman is considered as a

general person without having specific knowledge of

Ayurveda. It has been taken 30 numbers of laymen as a

sample. Here expert is considered as an expertise

person in Ayurvedic domain. System denotes the

implemented expert system for domains with tacit

knowledge. The evaluation was based on investigating

humeral constitutions as per layman using two groups

considered for the evaluation criteria. The layman,

Ayurvedic expert and system are referred as L, E and

Sys, respectively.

The layman-Ayurvedic Expert and layman-System

interactions can be comprehended by a figure as in Fig. 5.

Arranging the setup as depicted in Figure 5 enables

E to compare the differences between the interactions

with layman-Ayurvedic expert and layman-System.

The Ayurvedic expert’s feeling towards the use of the

system and the layman for his/her humeral constitution

is evaluated thereafter.

The key feature required to evaluate in the system is

whether the system derives a conclusion equaling a

conclusion derived by an expert who works with the

same domain. Here, modeling behavior of a conclusion

derived from a particular selected domain in to a further

analysis is expected. In this sense, aspects viz was tested.

Fig. 5 The experiment control.

Whether the same conclusion derived both in the

system and the existing non modeled domain,

Whether reducing dependencies effected

conclusion differences.

By testing this aspect it can arrive at a conclusion

that the commonsense knowledge modeling system

works in an agreeable way with a domain expert.

9.1 Reasoning for Different Conclusion Made between the System and Ayurvedic Expert

It is expected that overall conclusion about the system

and expert modeling in such domain would be same. On

this assumption, the evaluation proved that the percentage

of same overall conclusion made by the system and the

Ayurvedic expert is 77% (Tables 3 and 4).

9.2 Reasoning for Knowledge Classification Ability in the System

The system has classified knowledge objectively by

giving numerical values (percentages of human

constitutions types) in all layman-systems interactions

(100%), which were not done by Ayurvedic experts in

layman-Ayurvedic expert interactions. Therefore

Ayurvedic expert could classify knowledge

subjectively without giving numerical measurements

(fine-tuning ability), which is insufficient to prove

fundamentals of Ayurveda. So this enables to justify

fine-tuning ability of the system.

Development of Commonsense knowledge Modeling System for Psychological Assessment in Clinical Psycho

52

Table 3 System testing: expert vs. system.

Vata Pitta Kapha Expert_decision

25.71 20.71 53.57 KV

32.95 23.86 43.18 VP

39.88 23.81 36.31 VP

27.65 46.1 26.24 KP

25.69 29.36 44.95 KV

33.58 24.09 42.34 KV

25.71 34.28 40 KP

32.21 31.54 36.24 KV

22.51 29.8 47.68 KP

20.37 30.56 49.07 PK

30.6 35.52 33.88 PK

29.71 17.39 52.9 KV

41.07 10.71 48.21 KV

34.5 32.16 33.33 KV

23.46 28.57 47.96 PK

35.27 30.77 33.97 KV

42.36 36.11 21.53 VP

23.01 35.71 41.27 PK

47.94 19.86 32.19 KV

14.03 35.96 50 PK

19.15 36.88 43.97 PK

22.46 25.36 52.17 PK

40.47 26.78 32.74 PK

30.28 29.58 40.14 KV

12.71 44.92 42.37 PK

11.18 40 48.82 PK

11.24 40.24 48.52 PK

23.44 26.9 49.66 PK

17.09 36.75 46.15 KV

33.09 30.15 36.76 KV

9.3 Reasoning for Further Analysis Ability in the

System

System has given further explanations for derived

answers such as possible mental diseases,

predominated constitute type, in dominated constitute

type and it was about 100% of system-user interactions.

But Ayurvedic expert could not give further analysis

about derived answers as subjective measurement and

it was about 0% of Ayurvedic expert- user interactions.

This is proved by the user preference of the system

in reasoning the derived answers.

It has been observed that only 77% of conclusions

made by the sample have been emulated with both

system and Ayurvedic expert. Difference of 23% has

Table 4 Comparission of conclusions: expert vs. system.

Vata Pitta Kapha Expert_decision Conclusion

25.71 20.71 53.57 KV matched

33.58 24.09 42.34 KV matched

25.71 34.28 40 KP matched

32.21 31.54 36.24 KV matched

22.51 29.8 47.68 KP matched

20.37 30.56 49.07 PK matched

30.6 35.52 33.88 PK matched

29.71 17.39 52.9 KV matched

41.07 10.71 48.21 KV matched

34.5 32.16 33.33 KV matched

23.46 28.57 47.96 PK matched

35.27 30.77 33.97 KV matched

23.01 35.71 41.27 PK matched

47.94 19.86 32.19 KV matched

14.03 35.96 50 PK matched

19.15 36.88 43.97 PK matched

22.46 25.36 52.17 PK matched

30.28 29.58 40.14 KV matched

12.71 44.92 42.37 PK matched

11.18 40 48.82 PK matched

11.24 40.24 48.52 PK matched

23.44 26.9 49.66 PK matched

33.09 30.15 36.76 KV matched

been shown due to model refinement process carried

out by the Principal Component Analyzer. This leads to

the reduction of the dependency among questions in the

questionnaire. In normal consultancy process of

classification of humeral constitutions, Ayurvedic

expert may ask repeated questions by mistake due to

large number of consultations. In current practice

Ayurvedic expert can identify constitute type of a

patient subjectively. But classifying constitutions type

in percentages enhances the system. This leads to

convince the fundamentals of Ayurveda according to

classification of humeral constitutions. According to

fundamentals of Ayurveda in classifying humeral

constitution types, it has been stated that all

constitutions types consist of a combination. Possible

mental diseases that can be happened due to

predominated humeral constitution type have been

observed. But system gives a chance of handling that

part which enhances to measure the effect of minimum

Development of Commonsense knowledge Modeling System for Psychological Assessment in Clinical Psycho

53

constitution type for a mental disease.

10. Discussion

In this approach the domain experts are encouraged

to present their knowledge to construct more useful

questionnaire. However, different experts may propose

different questionnaire since their emphasis of domain

knowledge is different. At present the system is based

on one expert view of the domain knowledge.

Eventually PC analysis will be done on that knowledge

and generate the appropriate fuzzy membership

functions for classifying knowledge. Reasoning for

classified knowledge has been achieved by expert

system technology.

The key feature required to test in the system the

authors developed is whether the system represents

modeling commonsense knowledge, which is

considered as inconsistent process in real world

applications. At the model refinement stage 25

principal components have been identified using 100

laymen. This was due to the dependencies among

questions in the questionnaire. Further, this leads to the

reduction of dependencies among the questions in the

questionnaire. The evaluation of model for modeling

commonsense knowledge, was carried out using a

group of 30 laymen by an Ayurvedic expert. The

knowledge classification process has been done in

terms of objective measurement. The selected

evaluation of recognition of humeral constitutions has

been classified in to vata, pitta and kapha in

percentages (objective measurement). This stage is

directly integrated with proceeding model refinement

stage. Reasoning for objective measurement has been

further investigated. At this stage the authors

concluded that overall investigation of humeral

constitutions leads to several approaches such as

possible mental diseases, dominated humeral

constitution type. It was identified that modeling of

commonsense knowledge in existing expert systems is

not sufficient.

The overall system facilitates for a user in modeling

tacit knowledge that has not been modeled in existing

mechanisms. This is considered as inconsistency and

unable to extract useful conclusions. Further total

observations defined on a philosophical theory, which

is based on commonsense knowledge, cannot be

obtained. In the evaluation process of the system,

classification of humeral constitutions in current

practice of Ayurvedic medicine has been taken into

account. The current practice of classification of

humeral constitutions is based on Ayurvedic theory

called prakuthi pariksha. But certain observations

defined on this theory cannot be obtained.

The performances of the system have been

compared with an Ayurvedic expert using the

observations derived from a practice of classification

of humeral constitutions. Similar type of conclusions

made by both system and Ayurvedic expert is about

77%. Ayurvedic expert identified only a humeral

constitution type where as system identified total

humeral constitutions types in percentages. Further

reasoning for derived conclusions has given only by the

system such as possible mental diseases, constitutions

types and predominance constitution type.

11. Conclusions

The commonsense knowledge modeling system in

clinical psychology for Ayurvedic medicine can be

used for recognition of human constituents and its

possible mental diseases. Knowledge modeling

approach for modeling commonsense knowledge in

psychological assessment enables holistic approach for

clinical psychology. The system has been reached the

objectives of finding type of dosa (constituent type:

vata, pitta, kapha) in percentages, dominant type of

dosa and possible metal disease based on type of dosa.

The users of the system are not expected to hold

knowledge in statistical or artificial intelligence

techniques. This system can also maintain history of

patients for research related human constitutes. It

should be noted that with the help of Artificial

Intelligence technologies the authors have improved

Development of Commonsense knowledge Modeling System for Psychological Assessment in Clinical Psycho

54

the correctness of the decision making process in

relation to the use of traditional questionnaire for

psychological assessment in clinical psychology

integrated on Dosa in which one of the three

root-causes of unskillful or un-wholesome actions

(akusala-mula) and prakurthi pariksha in clinical

psychology of Auyvedic medicine. This eliminates the

inconsistencies and repetitiveness of answers and also

provides a means for explanation of reasons for

answers. The system can be further developed as a

comprehensive learning system with access to the

Internet. Evaluation of the system has shown 77%

accuracy.

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Journal of Health Science 2 (2014) 56-61

Isolated Gross Hematuria or Associated to Acute

Retention of Urine as a Sign of Urologic Malignant

Pathology

Angel Tomas Ibáñez Concejo, Marco Antonio Castillo, Juan Sanchez-Verde Bilbao, Jorge Short Apellaniz,

Ambar Deschamps Perdomo and Joaquin Garcia Cañete

Emergency Department, Fundación Jiménez-Díaz Hospital, Madrid 28760, Spain

Received: December 30, 2013 / Accepted: January 16, 2014 / Published: January 31, 2014.

Abstract: The causes of IGH (Isolated gross hematuria), as the only symptom or associated with ARU (acute retention of urine) caused by clots in the urinary tract in patients who do not have a previous diagnosis of urological malignant pathology and to study the immediate mortality in patients with that sign are described. A descriptive observational study of the etiologies of patients shows the above mentioned symptomatology from the 1st of January to the 30th of June of 2008 in the Emergency Department which received follow-up treatment up to December 2010. It also describes the mortality before the definitive diagnosis and the days between receiving attention in the Emergencies Department and the diagnostic tests. One hundred and four cases with the criteria described above were evaluated. Of these, 20.0% turned out to have bladder, prostate or kidney cancer; the bladder being the most affected organ. Of all the pathology, benign and malignant, the most frequent one is the benign hypertrophy of the prostate (49.8% of the total). Of the total, 4.8% of the patients died in the following weeks before finishing the diagnostic study. Isolated gross hematuria is a clinical symptom closely related to urological malignant pathology and it does not have an insignificant mortality rate in a short period of time. For these reasons it is necessary to accelerate the diagnostic tests as soon as the patient presents the symptom.

Key words: Gross hematuria, bladder cancer, prostate cancer, benign hypertrophy of the prostate, urothelioma.

1. Introduction

Gross hematuria is defined as red-coloured urine or

the presence of more than 100 red cells per field in the

urine sediment, being a common cause of treatment in

the Emergency Department. Hematuria means there is

bleeding in the urinary tract, upper or lower.

Gross hematuria can appear as a clinical sign within

a syndrome, appearing in the context of an acute pain in

the renal flank or fossa as in acute renal cholic; and it

can be associated with fever, dysuria and urinary

frequency in a urinary infection or a trauma in the renal

flank. The hematuria which is more frequently

associated with malignant pathology is on the other

hand more silent and painless and only when the

Corresponding author: Angel Tomas Ibáñez Concejo, M.D., Ph.D., research fields: emergency medicine and urology. E-mail: tomasibanezconcejo@msn.com.

hematuria is very clear might it entail the presence of

clots that block the urinary tract and create intense pain.

There were several studies that dealt with the

etiologic cause of hematuria, but only a few of them

detailed in what percentage of these patients who had

already a diagnosis of urological malignant pathology.

Clinicians on their everyday practice know that many

patients consult after a prostate or bladder surgery or

after undergoing an aggressive treatment because they

are still bleeding or are patients already diagnosed of

cancer and this is progressing or recurring. These

groups of patients have a known malignant cause of

hematuria and have had diagnostic protocol carried out,

and they should be distinguished from recent cases of

hematuria, in which the cause is unknown and could be

benign or malignant. Why do the authors need to make

this distinction? Well because failing to do so might

DAVID PUBLISHING

D

Isolated Gross Hematuria or Associated to Acute Retention of Urine as a Sign of Urologic Malignant Pathology

57

lead to an overestimation of neoplasic causes and what

is really important is to know the probability for a

hematuria to be finally secondary to a malignant

process.

Another important issue is BPH (benign porstatic

hyperplasia) a very prevalent pathology in males over

50 years that in some occasions presents with gross

hematuria. One might consider that patients with BPH

should not be included as cases of undiagnosed

hematuria, but due to its high prevalence, every patient

with this diagnosis should undergo the same diagnostic

tests as any patient is presenting a first episode of gross

hematuria, therefore they have not been excluded from

the study.

Finally, it is true that gross hematuria is rarely so

great as to generate haemodynamic instability of the

patient but it can also hide a severe pathology that has

to be diagnosed and treated early and appropriately.

Given its relation to cancer and it is not insignificant

mortality rate, as will be seen in the study, gross

hematuria should be dealt with in a protocolised

manner as a warning symptom.

2. Methods and Materials

A descriptive study was done of IGH (isolated gross

hematuria) or ARU (acute retention of urine) cases

seen during the first 6 months of 2008 in the

Emergency Department of the authors’ hospital.

Hematuria in other clinical scenario, such as a trauma,

renal colic or urinary track infection, was excluded.

The sample was selected from the medical-surgery

area of the Emergencies Department between the 1st of

January and the 30th of June, 2008. Pediatric,

gynecological or of talmological emergencies which in

the hospital are dealt with in other departments were

excluded. This gives a total of 28,173 cases, of which

153 had a diagnosis of IGH (133) or AUR (20).

All those already diagnosed with a urological

malignant pathology were excluded (49 cases), given a

total of 104 cases included in the study.

Search made on hospitals records, INDRA® data

base, for the final diagnosis was used to complete the

necessary information.

The variables that were studied were: age, sex,

smoking habits at any stage in life, time lapsed between

their episode in the urgency department and the exact

date of the diagnosis, the final diagnosis and in the case

of malignant pathology necessary treatment and

mortality.

3. Results

Overall gross hematuria represents 0.54% of all

visits to the emergency department, 104 patients met

the study selection criteria. The average age at

presentation was 70 years with a median of 77 years,

86.5% of cases presented on man (Table 1). Within the

malignant pathology group, the youngest patient was

61 years old and in the benign group there were 13

patients under that age (the most common pathology

was the BPH with 6 cases).

96.16% (100 patients) of the cases were derived to

external urology consultations and 3.84% (four

patients) were hospitalized for an inmediate study. Two

patients did not turn up for their urology appointments

and five of them died before finishing the study.

Of the patients who died, two of them died when

they were hospitalized in the urology department days

after arriving at the Emergency Department with the

diagnosis of hipovolemic shock and urinary sepsis.

And three patients who were not hospitalized initially

died of another cause, two in the hospital with the

diagnosis of ischaemic stroke and congestive heart

failure, and the other patient in another hospital with

the diagnosis of heart failure.

In 21 (20.19%) cases the final diagnosis was a

malignant neoplasia, with bladder cancer (15 cases)

followed by prostate adenocarcinoma (three cases) and

Table 1 Sex description.

Sex N %

Males 90 86.5

Females 14 13.5

Total 104 100.0

Isolated Gross Hematuria or Associated to Acute Retention of Urine as a Sign of Urologic Malignant Pathology

58

kidney neoplasia (three cases) and only one case of

uretral urotelioma (Table 2).

Of the 15 bladder cases 14 were urotelioma and one

carcinosarcoma. Of the three kidney cases, two of them

were clear cell carcinoma and one of them a renal

pelvis urotelioma. The staging is described in Table 3.

In 20 (95%) of the neoplasias cases were described

in males. 15 (71.4%) of them with a malignant disease,

and a 52% of the patients with BHP or ARU did smoke

or had smoked at some stage in their lives (Table 4).

To measure the time elapsed since the patients were

discharged from the Emergency Department to the date,

the final diagnosis was established, and the median

delay was used and turned out to be 140 days; in the

case of a malignant pathology the number decreased to

a median of 71 days (Table 5).

In 73.08% of the cases there was no malignant

pathology, the most common being BHP, infection of

the urinary tract, nonspecific hematuria, urolithiasis,

and benign bladder pathology. BHP represents 49.80%

of the total of benign and malignant pathology.

The rest correspond to the patients who died (4.8%)

and 2% whose cases could not be followed up.

As far mortality data, five patients died before

completing the study, corresponding to 4.8% of the

hematuria cases. Additionally, 15% of the patients that

were diagnosed with malignant pathology (three cases)

died in the first year after the final diagnosis.

Table 2 Final diagnosis.

Final diagnosis N %

Bladder cancer 15 14.42

Kidney cancer 3 2.88

Prostate cancer 3 2.88

Benign prostatic hyperplasia 51 49.03

Died before finishing the study. 5 4.80

Hematuria due to oral anticoagulation 1 0.96

Benign bladder pathology 5 4.80

Estenosis uretral 1 0.96

Infección tracto urinario 8 7.69

Litiasis 3 2.88

Trauma 1 0.96

Erectile dysfuction 1 0.96

Nonspecific hematuria/Not followed 7 6.73

Total 104 100

Regarding treatment of patients with malignant

pathology (Table 6), of 21 patients, 19 received surgery,

some of them with coadjutant treatment that was not

revised, and one patient received quimiotherapy and

one patient radiotherapy.

4. Discussion

Clinical guidelines indicate that hematuria must be

investigated in all cases [1] except for the so called

benign hematuria in which these can be found

Table 3 Bladder cancer who staging.

Bladder Cancer Stage N %

STAGE I 3 21.4

STAGE II 4 28.6

STAGE III 3 21.4

STAGE IV 4 28.6

Total 14 100

Table 4 Smokers description.

N %

Smokers 55 52.9

No smokers 38 36.5

Unknown 11 10.6

Total 104 100

Smokers in malignancy pathology group N %

Smokers 15 71.4

No smokers 4 19

Unknown 2 9.5

Total 21 100

Table 5 Time passed since the patients were discharged from the emergency department to the date the final diagnosis.

Percentile, minimum and maximum Number of days Mediana 140.00

25 percentile 48.00

75 percentile 210.00

Minium 3.00

Maximum 814

Table 6 Definitive treatment in malignancy pathology group.

N %

Only chemoterapy 1 4.76

Surgery 19 90.48

Only radiotherapy 1 4.76

Total 21 100

Isolated Gross Hematuria or Associated to Acute Retention of Urine as a Sign of Urologic Malignant Pathology

59

menstruation, intense physical exercise, a viral process

or a trauma [2-4] and even in these cases observation is

required [5]. The main reason for such a detailed study

is the high relation between hematuria and urological

cancer, even in microhematuria, although is at least

four times less frequent (compared to gross hematuria).

Gross hematuria is the initial symptom in 85% of

bladder cancer cases and in 40% of renal cancer [6].

According to several studies finding malignancy

after a first episode of gross hematuria varies from 9%

to 44% [7], with a big variety in the methodology used

[8]; even in the studies of microhematuria the

discovery of malignancy varies from 2.5% to 13% [1,

6]. In the study, malignancy was observed in 20% of

the cases, excluding patients that already had a prior

diagnosis of neoplasia. If they had been included, the

total would have risen to 45% of the cases.

Bladder cancer is the principal cause of malignancy

in the study as in other studies, way ahead of prostate

and kidney cancer [3]. As for the kidney tumors, even

though the three classic signs of kidney cancer are:

hematuria, pain or the appearence of an abdominal

mass, they only appeared in 9%-16% of cases, with

isolated hematuria [9] appearing on many occasions.

So even though thinking about bladder cancer, the most

prevalent, talking about hematuria and malignant

pathology, kidney cancer should be taken into account,

because it is being more aggresive in its evolution.

There are risk factors for malignancy that require a

more aggressive study in patients with hematuria:

smoking habits, occupational exposure to chemical

agents (benzene and aromatic amines), age over 40,

recidivant urine infections, a clinical history of

analgesic abuse, pelvic irradiation in the past or

previous gross hematuria [1, 4, 10]. As regarding age,

some studies do decrease the age to 35 [4, 9]. Gross

hematuria on its own is already a risk factor, although it

will be more probable if other risk factors are added.

Only a few authors say that gross hematuria can be

considered benign in women under 40 or when there

are clinical signs of urine infection and a positive urine

culture [11]. Of all the risk factors the authors have

only described smoking habit, finding a higher

prevalence of patients with smoking habits in the group

of malignancy as previous studies do.

Fortunately, the greatest percentage of hematuria

corresponded to BPH, which was secondary to the

vascular congestion in the prostate gland and delated

veins in the bladder neck [9]. In previous studies this

percentage ranged from 13.5% to 25% [12, 13], but it is

higher in the study (48%), it may be due to the fact that

other studies did not distinguish between

microhemturia and gross hematuria and that in the

study patients with previous diagnosis of tumoral

pathology were excluded, which underestimated the

total, and was not the case for patients who had BHP

for reasons set out earlier.

In the authors’ results, it might exists an

underestimation of gross hematuria as the presenting

sing of renal disease, blood dyscrasia or metabolic

alteration, although pediatric age had been

intentionally excluded from the study, since these

pathologies often showed microhematuria [9]. In

previous studies of gross hematuria, the renal origin of

it showed low percentages. At any age, a blood work is

always recommended in order to evaluate creatinine

levels and renal function.

It is worth to remind that gross hematuria is a clinical

scenario in which the clinician can make lots of

mistakes. The first is to underestimate the relevance of

hematuria once it has been resolved; it is important to

note that in malignant pathology hematuria is normally

intermittent, and this could explain the long time

elapsed between the first symptom and the final

diagnosis [5]. Another frequent mistake is to think that

it is due to anticoagulant therapy. The authors results,

as well as in others, this etiology is very infrequent,

rather acts as a trigger in patients with an underlying

cause [4, 10, 12]. Patients on anticoagulation therapy

should not be excluded from investigations. Another

frequent mistake is to attribute hematuria to a urine

tract infection, some obsolete clinical guidelines

Isolated Gross Hematuria or Associated to Acute Retention of Urine as a Sign of Urologic Malignant Pathology

60

suggest giving antibiotics to those patients who are

diagnosed IGH; the results of this study and others

suggest that this is not justified because such infections

represent only 7.6% of the causes [14]. It is also a big

mistake not to study patients who has already been

diagnosed with a benign urological pathology which

could have hematuria as a symptom, the most frequent

of which is benign hypertrophy of the prostate. That is

why it has been included in the study, unlike previously

diagnosed malignant pathology. Given the high

prevalence of BHP, a concomitant malignant cause is

not excluded, just as one does not assume a

hemorroidal pathology as a cause of rectorragia

without ruling out malign pathology via colonoscopy.

A limitation of the study is that it is not a

multicentric study with the corresponding population

similarity. But it can be considered as a multicentric

study, because it involves 400,000 inhabitants of

different areas of Madrid in the population area, with a

20% population of immigrants, and with an enormous

variety of population from all over the world. In this

sense, studies from the USA Afro-Americans and Latin

Americans have shown to have a greater predisposition

to urological malignant pathology.

The authors think that one of the most relevant data

is the 4.8% of mortality before diagnosis although it is

certainly difficult to explain, but suggest the following

possibilities: the patients age (mean age 70 years), the

high comorbility, the fact that many of them had lung

pathology due to their smoking habit and finally the

delay of 95 days as an average before a final diagnosis

is reached.

Some authors describe as criteria for hospitalization

a hematocrit fall and/or the presence for AUR [15].

For all the above reasons, the authors suggest that

gross hematuria should always be investigated and as

soon as possible because it can be the first sign of a

urological malignant pathology in many cases, and it

can be a multidisciplinary task involving primary care

physicians, emergency doctors, nephrologists and

urologists [1].

It does not seem sensible then not to be aggresive in

an early diagnosis. It is not justified, from any point of

view including the economic cost, because diagnosis

and treatment at an early stage, is six times cheaper

than in patients with a more advanced disease [8].

Diagnostic protocols adapted to the characteristics of

each institution should be drawn up in order to have a

first valoration from the urologist within a matter of

days after being seen in the Emergency department.

The most recent guidelines recommend the study of

the lower urinary tract with an ultrasound and

cystoscopy and the upper urinary tract with other

diagnostic imaging study (tomography, ultrasound, etc.)

although there is certain controversy because each

imaging test has different sensitivity and specificity for

each pathology; always including both, upper and

lower tracts [1].

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