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COMPARATIVE STUDY OF MANUAL STEREOTYPIES IN RETT

SYNDROME AND AUTISM –MOVEMENT QUANTIFICATION

ABSTRACT

Stereotypies are defined as involuntary movements, coordinated, repetitive,

rhythmic, and with no specific objective. Autism and Rett Syndrome (RTT) have

significant phenotypic overlap, and both are classified as pervasive developmental

disorders. Hand stereotypies are common in both pathologies. Our aim is to

determine quantitatively if they are really different as they seem to be by single

observation. In order to characterize quantitatively stereotypic movements we

designed a study based on 2d video capture and kinematic analysis. We

determine the velocity, the frequency, the displacement, the extent, the duration

and the number of stereotypies in both pathologies, RTT and Autism, in a

population of 9 patients 4 with RTT with MECP2 mutation and 5 with Autism. The

stereotypies of Autism, are faster, more repetitive, more extent and with a higher

displacement, they also last less time and occurs less often than the stereotypies

of RTT. KEYWORDS – Movement disorders, Stereotypies, Rett Syndrome, Autism, 2D Movement Video

Analysis, Movement Quantification

INTRODUCTION

Stereotypies are defined as

involuntary movements, coordinated,

repetitive, rhythmic, and with no

specific objective. They can last

seconds to minutes, occur in clusters,

several times a day and are associated

with periods of stress, excitement,

fatigue or boredom. The Diagnostic

and Statistical Manual of mental

Disorders criteria for stereotypies

requires repetitive, nonfunctioning

behaviors that are present for more

than 4 weeks and that interfere with

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normal activities or result in self injury

(DSM-IV-TR 4th ed.).

Stereotypies are classified into

two major categories according to the

underlying cause. They can be primary

or secondary, on the basis of the

presence or absence of other

development problems, respectively.

Primary stereotypies can be present in

children with normal development and

they are divided in other three sub-

categories as: common behaviors

(e.g., rocking, head banging, finger

drumming, pencil tapping, hair twisting)

and two forms with atypical or complex

behaviors—head nodding and complex

motor movements (e.g., hand and arm

flapping/waving) (Singer, H., 2009).

Secondary stereotypies are common in

children with neurobehavioral

syndromes, such as the autism

spectrum disorders, Rett syndrome,

cognitive deficits, and sensory

deprivation, neurodegenerative

disorders, inborn errors of metabolism,

drug-induced conditions, infection,

tumor, or psychiatric conditions.

The mechanism for

development of stereotypies remains

unknown, but the involvement of the

cortico-striatal-talamo-cortical

pathways, as well the dopaminergic

system seem to be implicated in the

pathophisiology of the stereotypies.

(Kates, W et al, 2005 and

Muthugovindan, D. and Singer, H.,

2009). In children with autism they may

be correlated with atypical prefrontal

cortical development (Johnson, M H et

al, 1991), frontal lobe and cerebellar

vermis volume (Militerni, R. et al,

2002). Stereotypies in Rett syndrome

may relate to structural and functional

abnormalities of the cortico-subcortical

pathways (Carter JC et al, 2008).

Rett syndrome (RTT) is the

expression of a genetically determined

disease, and up to 96% of classic RTT

patients have a mutation located within

the Methyl-CpG Binding Protein 2

(MECP2) gene on the X chromosome

(Amir RE, et al, 1999 and Girard, M et al,

2001). However, there are clinically

diagnosed classical and atypical RTT

cases in which no mutation was

identified. MECP2 mutations are rare in

other disorders (eg, autism), indicating

that MECP2 is only one of many genes

that could contribute to the large

spectrum of neurodevelopmental

disorders (Gonzales, M et al, 2010).

Autism and Rett Syndrome have

significant phenotypic overlap, and

both are classified as pervasive

developmental disorders, but the

genetic basis of autism is stills unclear

and likely involves multiple genes

(Gonzales, M. et al, 2010).

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Rett syndrome occurs almost

exclusively in girls (Amir, RE et al,

1999), males, rarely, have been

reported with the Rett-like phenotype

(Weaving et al., 2005).

In RTT psychomotor

development (PD) is normal until 6-18

months of age, followed by a period of

regression of PD. The first symptoms

appear in the form of psychomotor and

mental retardation and stereotyped

movements of hands and other body

areas associated with functional loss of

use of hands, decelaration of head

grow. The neurological symptoms

include worsening spaticity and

distonia, gait dyspraxia, scoliosis,

epilepsy, disordered sleep and

hyperventilation (Goldman, S and

Temudo T, submitted 2011).

Manual stereotypies are a

hallmark of RTT, and one of its

necessary and most important

diagnostic criteria (Temudo, T. et al,

2007). In most of the cases they are

associated with or follow the

disappearance of purposeful hand

movements, although they can be

present before developmental

regression begins (Einspieler, C. et al,

2005 and Temudo, T. et al, 2007).

Stereotypies in RTT can be in the

midline, with symmetrical movements

of both hands, (washing, clapping,

tapping, wringing, hand mouthing), or

with hands apart more frequently each

hand performing a different movement

such as hair pulling with one hand, the

other tapping the trunk (Temudo, T et

al, 2008).These repetitive almost

continuos and compulsive movements

disappear during sleep and may

aggravate with anxiety (Temudo, T. et

al, 2007). In general, mutation-positive

patients had more diverse stereotypies,

which usually diminished after the age

of 10 (Temudo, T. et al, 2007).

Autism Spectrum Disorders are

a group of conditions that are

neurodevelopmental in origin and first

observed in infancy (Ben-Itzchak, E. et

al, 2008; and Matson, JL, et al, 2007).

The diagnosis is clinical and according

DSM IV, based on a behavioral

disorder characterized by the inability

to establish social and interpersonal

relationships, difficulties in verbal and

nonverbal communication, as well as

patterns of behavior, interests and

activities are restricted, repetitive and

stereotyped.

Each child with autism has

his/her own repertoire of stereotypies,

which can evolve with time, and is

repeated always in the same manner

(Muthugovindan, D. and Singer, H.,

2009). However, some primary

movements (bilateral flapping or

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rotating the hands, fluttering fingers in

front of the face, flapping/waving arm

movements, and head nodding) tend to

predominate (Werry, J.S. et al, 1983).

Hand/finger stereotypies and gait are

especially suggestive of autism

(Goldman, S et al, 2008).

The target and the velocity of a

voluntary movement are impaired by

the movement disorders. They

influence the posture, the presence of

abnormal involuntary movements and

the performance of normal-appearing

movements (Zinner, S. and Mink, J.,

2010).

Stereotypic behaviors may be

verbal or nonverbal, fine or gross

motor-oriented, as well as simple or

complex, and they may occur with or

without objects (Cunningham, A. and

Schreibman, L, 2008). Stereotyped

movements with object manipulations,

includes spinning or twirling items, but

their manipulation is not required to be

identified stereotypies as such. (Zinner,

S. and Mink, J., 2010) Stereotypies

typically are present before 3 years of

age and they can diminish or persist

into adulthood (Zinner, S. and Mink, J.,

2010). Autism and low IQ have additive

effects on the number and variety of

stereotypies. (Goldman, S et al, 2008)

Stereotypies had correlation with the

severity of the autism and cognitive

impairment, both indexes of the extent

of underlying brain dysfunction

(Goldman, S et al, 2008).

The Analysis of the human body

motion is a challenging problem

because it is an extremely highly

flexible structure that has movements

in many plans; it can twist and bend in

many degrees of freedom. How to

extract human motion has been an

important research topic in computer

vision. In addition, the variety of

luminance, noise induced by devices

and self-occlusions of the human body

complicate the movement analysis

process. To address this complex

problem, some investigators used

marker-based methods to evaluate

human body motion for clinical

diagnosis (Li, et al, 2002)., however,

these approaches can only work for a

few simple human motions.

In this work we intend to study

and compare stereotypies of children

with autism and Rett syndrome. We will

characterize these behaviors according

to the type of motion, duration, variety,

frequency and velocity. We also intend

to carry out research of

electroencephalography in order to

identify the possible abnormal electric

activity during the stereotyped

movements. We will use the 2D

analysis of the video images and

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extract the quantification of stereotypic

movements.

With the data obtained we aim

to achieve a more complete and

accurate knowledge of stereotypes and

indicate the possibility of developing

this approach for early diagnostic

screening of RTT and autistic patients.

SUBJECTS AND METHODS

1) Patients

In this work we propose a study

with children diagnosed with Autism

and Rett syndrome. The initial plan

was to include 18 children, 6 with

Autism and 12 with Rett Syndrome (6

with a MECP2 mutation). However,

due to the selected patients age range

(6 to 16 years), only 8 patients with

Rett Syndrome and 9 with Autism were

studied.

Our final population is

composed by 4 patients with RTT with

identified MECP2 mutations, and 5

patients with Autism. The other

patients were excluded due to the

absent of stereotypies during record or

due to occlusions of the hands, which

did not allow image tracking.

All the Rett patients fulfilled the

revised criteria for Rett Syndrome

(Hagberg, 2002 and Neul et al 2010).,

and all autistic patients met DSM IV

Criteria for autistic disorder. The

IQ’patients was assessed using the

Grifftiths Scale for mental

development, due to the lack, or

underdevelopment of language

(Grifftiths, R., 1992).

The parents of all children

signed an informed consent for

participation in this study. The study

was approved by ethical commission

for health of Centro Hospitalar do

Porto.

2) Methods

For each child a 30 minutes

video-EEG acquisition was performed

in order to capture stereotyped

movements.

Landmarks were attached to the

patient upper body and a video

electroencephalogram (EEG) system

with a commercial camera was used to

synchronously register EEG and video

during stereotypies. All patients with

Rett Syndrome were recorded with the

referred setup. Each finger and parts of

the upper limb were color-coded to

simplify video tracking algorithms (Li, et

al, 2002), in order to enable the 2D

video analysis.

Finger landmarks were elastic

rings and positioned in the proximal

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phalanx, near to the proximal inter-

phalange joint.

A marker with a fixed dimension

(5 x 7.6cm) has been attached to the

child's clothes in the anterior and upper

chest that should be visible during the

entire shooting that should be

performed parallel to the camera plan

in order to capture the prevailing

movement of the hands.

The EEG study was done

simultaneously with the video, in order

to correlate EEG signals with

stereotyped movements.

Autistic children did not tolerate

EEG electrodes nor the referred finger

markers. Nevertheless, movement

analysis could be performed manually.

The videos were analyzed and the

segments with stereotypies

(movements of interest – MOI) were

cropped.

With this process we obtained 88

MOI: 44 from 4 Rett patients and 44

from 5 autistic patients. Subsequently,

the videos were processed manually

using MaxTRAQ®,(Innovision Systems,

USA) which allows the tracking of

selected finger markers or points at the

hands. The tracking target was mostly

the middle finger, and sometimes to

avoid occlusions, other fingers or the

wrist were chosen in both hands. The

resultant movement data was saved in

a “c3d” file and a video with the

movement tracking embedded was

generated.

These files were analyzed using a

custom program on Matlab®

(Mathworks, USA) platform from which

position in xx and yy axis and speed

profiles of both hands were computed.

To enable a frequency analysis, the

speed data was filtered using two

steps: firstly the mean of speed was

subtracted from the speed vector to

reduce the impact of the DC (0 Hz).

Secondly the speed data was filtered

with a bandpass filter with lower and

higher cutoff frequencies of 0.5Hz and

10Hz, respectively.

For the movement displacement

analysis, we calculated in each MOI

the Euclidian distance between the

position of the tracked point and a

reference point. The results achieved

were filtered using the previous

described steps and a Fast Fourier

Transform (FFT) was applied to obtain

the frequency spectrum of stereotypy

movements.

The main frequency component

was compared to expected range

obtained by visual inspection of the

MOI.

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RESULTS

Table I - Characterization of Study Population

Patient Age (Year) Gender Mutation of

MECP2

Mental Age

(Griffiths)Regretion Epilepsy EEG

Ret

t Syn

drom

e

P1 11 Female Delection of exon 3 and

4 Unknown Yes Yes, controled with

medication

With paroxistic activity, but not correlated with

stereotipies

P2 8 Female T158N Unknown Yes Yes, controled with medication

Without paroxistic activity

P3 11 Female R294X Unknown Yes Yes, controled with medication

With paroxistic activity, but not correlated with

stereotipies

P4 13 Female R133C Unknown Yes Yes, controled with medication

With paroxistic activity, but not correlated with

stereotipies

Mean 10 Years

and 9 Months

Median 12 Years

Aut

ism

P5 8 Male Unknown 3Y e 0M Yes Yes, controled with medication Unknown

P6 10 Male Unknown 3Y 4 M No No Unknown

P7 6 Male Unknown 2Y 4 M No No Unknown

P8 15 Male Unknown 4Y e 1 M Yes No Unknown

P9 8 Male No 2Y No Yes, controled with medication

Without paroxistic activity

Mean 9 Years and 3 Months

Median 8Years

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Rett Syndrome (n=4)

Type of stereotypies No of Stereotypies in 30' No of Different Hand Stereotypies in 30' Total time of Stereotypies (s) Topografy Laterality, And Complexity

Visual Behavior

Patient 1 Interlacing fingers of one hand, hand at the mouth and cross a leg over the other 197 3 144,12 Hands separated, not symmetric, not at the

midline, Complex movements. No

Patient 2 Washing hands and clapping 69 2 70,44 Hands together, symmetric, at the midline. Single movement

No

Patient 3 Clapping and rubbing 64 2 55,44 Hands together, symmetric, at the midline. Single movement

No

Patient 4 Hand flapping, with fingertips together 112 1 105,4 Hands separated 1 always almost stopped, not symmetric, not at the midline. Complex

movements

No

Mean 111 Mean Time (s) 93,85 Median 58 Median Time (s) 87,92 Minimum 2 Minimum Time (s) 0,92 Maximum 31 Maximum Time (s) 37,56

Autism (N=5)

Patient 5 Flapping 33 1 13,76 Hands separated (++) and together,

symmetric, at the midline and not at the midline. Single movements

No

Patient 6 Flapping and trunk balance 25 1 11,4 Hands separated, symmetric, not at the midline. Single movements

No

Patient 7 Turn in and out, rubbing, flapping, one hand

at the Head and trunk balance. Hand stereotypies with object.

32 4 21,64 Hands separated (++) and together,

symmetric and not symmetric, at the midline and not at the midline. Complex movements

Yes

Patient 8 Oscillatory tapping, tapping, "cutting" one

hand with the other, finger tapping and one hand at the head

115 6 84,68 Hands together, mostly symmetric, at the midline. Complex movements

No

Patient 9

Tremor like movements, tickling the toy, clapping, flapping with one hand and the

other at the mouth, counting like movements with the finger and twirl the wrist and cross a

leg over the other. Hand stereotypies with object.

83 7 51,36 Hands together and separated, symmetric and not symmetric, at the midline and not

midline. Complex movements.

No

Mean 9 Mean Time (s) 42,27 Median 4 Median Time (s) 21,64 Minimum 1 Minimum Time (s) 0,44 Maximum 31 Maximum Time (s) 23,36

Table II – Number, duration and qualitative features of stereotypies in RTT and Autism.

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Graph 1 - Absolute value of de difference between

the mean velocity of left and right hands

Movement Features RTT (n=4) Autism (n=5)

Mean Velocity (pixel/s) 62,68 371,19

Median Velocity (pixel/s) 57,00 230,95

Maximum Velocity (pixel/s) 279,67 1797,76

Minimum Velocity (pixel/s) 0,37 4,66

Mean Frequency (Hz) 1,46 2,80

Median Frequency (Hz) 1,18 2,86

Maximum Frequency (Hz) 4,37 4,96

Minimum Frequency (Hz) 0,64 0,79

Mean Desplacement (pixel) 242,99 440,04

Median Desplacement (pixel) 152,99 287,15

Maximum Displacement (pixel) 1266,74 1891,19

Min Displacement (pixeis) 0,92 21,69

Mean Extent (pixel2) 2727,16 6164,88

Median Extent (pixel2) 607,16 3437,84

Maximum Extent (pixel2) 39668,74 45243,98

Minimum Extent (pixel2) 0,30 17,86

Table III - Quantitative Features of Stereotypies

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Graph 2 - Duration of moments of interest

Graph 3 - Frequency of both hands in RTT and Autism

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Graph 4 - Displacement of each hand during a MOI in RTT and Autism

Graph 5 - Extent of both hands in a MOI in RTT and Autism

A MOI was defined as a

sequence of stereotypies done

continuously with minimal interval of 3

seconds.

As we can observe in Table I all

the RTT patients, were girls. The age

of the children was identical in the

entire sample, the mean age at RTT

was 10 Years and 9 Months and the

median 12 years, in Autism the mean

was 9 Years and 3 Months and the

median 8 years. all the patients with

Autism were boys.

In our population all the girls

have MECP2 mutation, which is

different in all of them. The oldest girls

have more stereotypies (Patient 1 has

197 and patient 4 has 112) than the

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youngest (patient 2 has 64) as we can

see in the Table II. If we compare

patient 1 and patient 3, both with same

age (11 years) but with different

MECP2 mutation, Patient 1 has much

more stereotypies. In Table 2 Patient 1

has more stereotypies which occurs

during more time (144,12 s), than

patient 3 who has only 64 stereotypies

in 55,44 s. We can also observe that

patient 1 has more variety of

stereotypies, such interlacing fingers of

one hand, hand at the mouth and cross

a leg over the other, than patient 3 that

only has two different types: clapping

and rubbing. The topography, laterality

and complexity of stereotypies are

variable in the study population. In RTT

patients were observed stereotypic

movements with hands together, hands

apart, symmetrical, and asymmetrical,

simple and complex movements.

We find in our sample various

types of stereotypies that are common

in children with RTT such as:

interlacing fingers of one hand, hand at

the mouth, cross a leg over the other,

washing hands, clapping and rubbing.

But we also find other type which is

more uncommon: hand flapping, with

fingertips together. These movements

were found in patient 4, who has e less

severe mutation (R133C). All RTT

patients have epilepsy although none

revealed paroxistic activity

synchronous with the stereotypies on

the EEGs exams.

In the Table I are exhibit the

mean and the median ages of the

patients with autism in the study as we

can see both mean (9 years and

3months) and median (8 years) are not

very different from the same

parameters found in the RTT.

Analyzing table II it is notorious

the difference between the number and

variety of stereotypies performed by

patient 8 and by the patient 9.

Curiously patient 8 has a severe

development delay, his mental age is 4

years and 1 month, and his real age is

15 years. Patient 8 was the child with

autism that made more stereotyped

movements, and some of them were

very complex and difficult to describe.

However patient 9 of our study has

some clinical features from RTT, such

as the type of stereotypies. The

research of mutation MECP2 was done

in this patient and was not found,

despite of the phenotypic similarity.

Patient 8 exhibited 5 types of

hand stereotypies as: oscillatory

tapping, tapping, "cutting" one hand

with the other, finger tapping and one

hand at the head. He did 115

stereotypies during 84,68 s, he

performed much more stereotyped

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movements and had more diversity

than the others patients, except patient

9 that exhibit also a large number of

stereotypies: 83 with even more

different types than patient 8. Patient 9

had stereotypies that resemble RTT,

tremor like movements, tickling the toy,

clapping, flapping with one hand and

the other at the mouth, counting like

movements with the finger and twirl the

wrist and cross a leg over the other.

However he had stereotypies with

object, as patient 7, which is

characteristic of autism. Patient 7 has

also other aspect characteristic from

Autism he looks to his hands when is

doing stereotyped movements Table II.

With exception of patients 7,8 and 9,

which had complex stereotypies, all the

autistic patients hand single

stereotyped movements.

As we observe in Table II RTT

patients had more stereotypies (mean

= 111) and they occur during more

time in the study 30 minutes (mean =

93,85 s), than the patient with autism

(mean of stereotypies = 9 and mean

time = 42,27 s), whose variety of

stereotypic movements was also

smaller.

In the Table III are represented

the qualitative features of stereotypic

movements in both pathologies. As we

can se stereotypies performed by

patients with Autism had more elevated

values of mean velocity (371,19

pixel/s), mean frequency (1,46Hz),

mean displacement (440,04 pixel) and

mean extent (6164,88pixel2), than RTT

patients: mean velocity (62,68 pixel/s),

mean frequency (2,80 Hz), mean

displacement(242,99 pixel) and mean

extent (2727,16 pixel2).

Graph 1 represents the absolute

value of the difference between the

mean velocity of the each hand in RTT

and Autism and as we can observe the

values corresponding to Autism are

almost always highest than those

corresponding to RRT.

As we observe in graph 3 the

time occupied doing a MOI was clearly

highest in RTT.

The Graph 3 represents the

mean frequency of both hands in RTT

and Autism, it is clearly that mean

frequencies of RTT are mostly between

1 and 2 Hz (median = 1,18 Hz), while

Autism frequencies are more scattered

and high (median = 2,86 Hz) than

frequencies or RTT.

Graphs 4 and 5 represents,

respectively the displacement and the

extent of the hands movements during

a MOI, which are both highest in

Autism than in RTT. This fact is also

represented in the Figure 1, the

displacement, represented by the

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green trace, and the extent is

represented by red trace, which was

represents the area where the hand

movement was done (Remi et al,

2011).

DISCUSSION

With this study we intended to

characterize and achieve a better

knowledge of stereotypies. As Rett

Syndrome is one of the best human

models to study movement disorders

(Temudo, T et al, 2008)., and exist an

overlap between the referred syndrome

and Autism (Gonzales, M. et al, 2010).,

these two pathologies seemed to

perform an interesting model to

compare stereotypies.

As we registered at the Table I,

none of the Rett patients had abnormal

cerebral activity during the

stereotypies. So we can predict,

although the limited size of our sample

that stereotypies may be not related

with abnormal cerebral activity, despite

of the majority of Rett patients have

epilepsy. Autistic patients had less

epileptic pathology associated; in our

sample only one child with Autism has

epilepsy diagnosed, which is controlled

with medication. But as was not

possible to document by EEG we

cannot excluded the possibility of the

occurrence of abnormal cerebral

activity during stereotypies on this

children.

By a simple observation,

stereotypies seem to be different in

Rett Syndrome and Autism, although

until today mostly only descriptive

studies were published.

Our aim was to study the

kinematic of stereotyped movements in

both pathologies in order to identify the

quantitative differences between them.

In order to achieve our aim we

performed a detailed analysis of some

movement features. So as we

predicted, stereotypies in Autism have

a high mean velocity (371,19 pixel/s)

than stereotypies in RTT (62,68

pixel/s), this shows that stereotypic

movements in Autism are faster than

the RTT movements.

The mean frequency in autism

(2,80 Hz) is approximately the double

of the mean frequency in RTT (1,46

Hz). This demonstrates that

stereotypies in Autism are more

repetitive than in RTT. These values

are not far from those described at only

Figure 1 ‐ Trace of the displacement and the extent (red) of the movement

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study found in our research. In that

study was analyzed the stereotypic

movements of a girl with RTT and their

results were not distant from ours.

They found a frequency movement of

1,2 Hz (Wright, M. et al, 2003).

By a simple observation

stereotypic movements of RTT seemed

to be less long, less extent and last for

more time. With our analysis we verify

that it occurred in our population.

So as we described stereotypies in

Autism are faster, more repetitive,

more extent and has a higher

displacement, last less time and occurs

less often than the stereotypies of RTT.

This could be explained by the

occurrence of more and more severe

neurological disorders in RTT, than in

autism, which affects the movement

performance. This last fact together

with the movement features

corroborates our hypothesis.

Limitations

The capacity of 2d images to study a

behavior that occurs in 3d can be

questionable, but some studies

approved the 2d capture, by comparing

the ability of this method with the 3d

images analysis and realized that

simple 2d images captured with a

commercial camera can be used to

kinematic studies with identical

accuracy (Wright, M. et al, 2003).

It was difficult to have always

standardized conditions, which allows

better comparison between subjects

and groups. Protocols for the filming

and assessment of activities have the

potential to counter these difficulties

and enhance the objectivity of video

assessment (S. Fyfe et all, 2007). In

our study we had this difficulty

especially with patients with autism, so

in upcoming studies will be important

predict these possibilities and had

protocols mores adapted.

Other important limitation was

the reduced population size, which not

allow us to had statistically significant

results and led the study to a more

observational perspective. Although

the results seem to be promising an

extensive study would be useful to

prove our results.

CONCLUSION

These initial results provide a

foundation for larger projects and the

first prospective observational data,

despite of these observations must be

confirmed in a larger sample (and

replicated by other groups).

As we expected there are several

differences between stereotypies of

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RTT and those of Autism, whose the

movement features studied

characterized them as faster, more

repetitive, more extent and with a

higher displacement, they also last less

time and occurs less often than the

stereotypies of RTT.

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