CVA VR AND TREADMILL TRAINING ANALYZING THE EFFECTS … · Cerebrovascular accidents (CVAs), occur as a result of loss of blood flow to the central nervous system as a result of a

CVA VR AND TREADMILL TRAINING

ANALYZING THE EFFECTS OF VIRTUAL REALITY AND TREADMILL GAIT

TRAINING FOLLOWING A CEREBROVASCULAR ACCIDENT

_______________________________________________________________________

An Independent Research Project

Presented to

The Faculty of the Marieb College of Health and Human Services

Florida Gulf Coast University

In Partial Fulfillment of the Requirement for the Degree of

Doctorate in Physical Therapy

_____________________________________________________________________

By

James R. Sauerwald and Hadeer Shwket

2017


APPROVAL SHEET

This independent research is submitted in

partial fulfillment of the requirements for the

degree of

Doctorate of Physical Therapy

________________________________ Hadeer Shwket

________________________________ James R. Sauerwald

Approved: April 2017

________________________________ Dr. Mollie Venglar, DSC, MSPT, NCS

Committee Chair

________________________________ Dr. Derek Lura, PhD Committee Member

The final copy of this independent research has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of

scholarly work in the above mentioned discipline.


Acknowledgements

First we would like to acknowledge the significant efforts of our faculty members

Dr. Venglar and Dr. Lura for their continued advice, support, guidance, and patience

throughout this study. We appreciate the countless evenings they took out of their time to

aid with supervising the study. Also thank you to Florida Gulf Coast University's Elaine

Nicpon Marieb College of Health and Human Services and the Whitaker College of

Engineering for allowing us to utilize your labs and equipment for our study. We would

also like to express gratitude to the FGCU Engineering students, Josiah Keime, Antuan

Madrazo, and Brandon Hays for being our fellow researchers in this study and assisting

with the Qualisys data collection and extraction, as well as all technical aspects of the

virtual reality. Most importantly thank you to our research participant and her family

members for their willingness to take the time out of their days to participate in our study.

And finally thank you to our family members for their continued support and motivation.

CVA VR AND TREADMILL TRAINING 1

Table of Contents

Abstract ........................................................................................................................... 2

Introduction ..................................................................................................................... 4

Methods ......................................................................................................................... 12

Data Analysis ................................................................................................................ 16

Results ........................................................................................................................... 16

Functional Gait Analysis ........................................................................................... 16

Six-Minute Walk Test ............................................................................................... 19

Spatiotemporal Gait Parameters ................................................................................. 22

Discussion ..................................................................................................................... 26

Functional Gait Assessment ...................................................................................... 26

Six-Minute Walk Test ............................................................................................... 27

Step-Length ............................................................................................................... 28

Cadence ..................................................................................................................... 30

Limitations ................................................................................................................. 30

Participant Feedback .................................................................................................. 31

Conclusion ..................................................................................................................... 32

References ..................................................................................................................... 33

Appendix: Virtual Reality Environments ...................................................................... 38


Abstract

Background: Cerebrovascular accidents (CVAs) have an adverse effect on

strength, balance, and gait, resulting in a number of functional ambulation deficits.

Previous studies indicate that with consistent gait training, participants effectively

increase gait velocity, as well as gait assessment functional outcome scores. Purpose:

The purpose of this case study was to examine the effects of treadmill gait training with

virtual reality (VR) on the functional recovery of gait in a participant affected by chronic

CVA. VR is a computer-simulated, interactive, multi-dimensional environment. The

purpose of the VR is to provide normal visual flow (optic flow) while walking in a

controlled environment (on a treadmill). Methods: The participant was a 24-year old

female who was 13 months post stroke. She participated in the study for 21 sessions over

14 weeks. She went through four sessions of initial assessments followed by gait training

sessions and finally two follow up assessments to track changes in her gait. An Oculus

head mounted stereoscopic display provided optic flow in the form of virtual

environments during gait training on a modified belt-driven treadmill. Physical Therapy

students provided facilitation to the participant while gait training on the treadmill with a

goal of 30 minutes of continuous ambulation. Data Analysis: The outcomes of the gait

training method were assessed: motion capture via Qualisys camera system, the

Functional Gait Assessment, and the 6-Minute Walk Test. Minimal detectable change,

percent changes, and Pearson Correlation Coefficients were calculated to assess

significance. Results: The study found improved gait velocity, step length, stride length,

cadence, FGA scores, & 6MWT scores throughout the study and also after the

intervention ceased. Conclusion: The findings of the study show promise in the


integration of virtual reality with treadmill gait training for rehabilitative purposes.

However, the results cannot be generalized to larger populations until further research is

completed.


Introduction

Cerebrovascular accidents (CVAs), occur as a result of loss of blood flow to the

central nervous system as a result of a hemorrhage or ischemia. CVAs are the fourth

leading cause of death in America, and one of the leading causes of long-term functional

deficits (Culebras et al., 2013). CVAs have an adverse effect on strength, balance, and

gait, resulting in decreased walking speed, decreased stride length, decreased cadence,

decreased safety, decreased joint power and delayed initiation of ambulation. All of the

aforementioned deficits in gait function due to CVA impair the ability of those affected to

ambulate in the community, and is of great concern throughout the rehabilitation process

(Mirelman, Patritti, Bonato, & Deutsch, 2010).

Johnannsen, Broetz, and Karnath (2006) report that approximately 60% of those

affected by CVA will experience deficits in both balance and posture during gait. Most

often, the resulting neurological deficits in those affected by CVA manifest in favoring

the strong (unaffected) side in the case of hemiparesis or hemiplegia, which results in an

asymmetrical gait pattern (Bowden et al., 2006). Favoring one side during gait results in

compensation in the form of abnormal weight-shifting, leading to asymmetrical limb

loading during gait (Balasubramanian, Bowden, Neptune, & Kautz, 2007).

Safe ambulation post-CVA is essential to reduce the risk of falls and subsequent

injuries and complications. Effective functional gait training is important in this at-risk

population. O'Sullivan (2014) enumerates a long list of reasons why individuals affected

by chronic CVA are at a 23% to 50% increased risk for falls: "sensorimotor deficits,

impaired balance, confusion, attention deficits, perceptual deficits, visual impairments,

behavioral impulsivity, depression, and communication problems.” Ada, Dean, Lindley,


and Lloyd, (2009) report that walking speed and walking capacity have both been found

to be reduced in individuals following a CVA. Whereas normal walking speed for the

community ambulating geriatric population is 1.3 meters per second, a reduced range

between 0.3 and 0.8 meters per second results following a CVA (Ada, Dean, Lindley, &

Lloyd, 2009). Walking capacity during a six-minute walk test is typically 576 meters for

males and 494 meters for females. Average post-CVA walking capacity is 250 meters,

with a range of 40 to 400 meters. Collectively, these ambulation deficits don’t allow for

safe community ambulation.

Gait patterns among those affected by chronic CVA have been strongly

correlated with reduced gait velocity, a reduction in the quality and adaptability of the

gait pattern overall, coordination and balance issues relative to weight shifting and

asymmetric leg loading during the gait cycle (Balasubramanian et al., 2007; Bowden,

Balasubramanian, Neptune, & Kautz, 2006; Goldie, Matyas, & Evans, 1996; Ada et al.,

2009). Bowden et al. (2006) have shown that the affected paretic leg will only perform

30% to 40% of the mechanical work through the gait cycle (versus an ideal of 50%), and

point out that losses in forward propulsion of the affected limb may not be as pronounced

as the differences in weight-bearing between limbs. Regardless of the primary deficit

associated with the paretic lower extremity, reductions in forward propulsion and the

ability to bear weight on the affected limb are functional deficits commonly addressed

during gait training activities (Bowden et al., 2006).

Treadmill training has proven to be an effective means of gait training, and assists

in decreasing energy expenditure and cardiovascular demands for individuals affected by

CVA (Lin, Hsu, Hsu, Wu, & Hsieh, 2010). Traditionally, CVA rehabilitation has


involved over-ground gait training, standard treadmill training, and body-weight

supported treadmill training (BWSTT). BWSTT has shown to be effective in improving

overall gait patterns (Visintin, Barbeau, Korner-Bitensky, & Mayo, 1998), but has not

been proven to be superior to over-ground training (Franceschini, Carda, Agosti,

Antenucci, Malgrati, & Cisari, 2009).

Virtual reality (VR) has become a beneficial tool in gait training, and in some

aspects superior to traditional methods with regards to gait function and balance (Pang,

2014). VR utilizes graphic images and simulated environments to provide participants

with continuous visual feedback regarding their performance in a “virtual world”. It has

been defined as the use of interactive simulations created with computer hardware and

software to present users with opportunities to engage in environments that appear and

feel similar to real world objects and events. (Weiss, Kizony, Feintuch, et al., 2006). It

allows participants to be supervised whilst experiencing simulated real-life scenarios.

Utilizing VR for gait training allows for challenging real-world scenarios such as public

spaces (parks, downtown sidewalks, and crosswalks) and busy retail stores. An infinite

number of other possibilities exist, limited solely by the imagination of software

engineers, with an emphasis on safety within the environment (Walker et al., 2010). VR

has been said to be a potentially beneficial intervention for CVA rehabilitation due to its

ability to provide a high dose of repetition, provide live feedback, be individualized and

motivate patients (Demain et al., 2013; Merians et al., 2002). However, research in this

specific niche of gait training has only recently come to light, and is presently limited in

both scope and quantity.


Optic flow (OF) succinctly describes the visual interpretation of movement within

the visual field (Lamontagne, Fung, McFadyen, & Faubert, 2007). OF as defined by

Kang, Kim, Chung, and Hwang (2012) is "the pattern of the visual information about the

direction and speed generated by the relative motion between a patient’s eye and the

surrounding environment." Functional gait at peak performance requires the integration

of balance (vestibular input and postural output), vision and proprioception (Harris,

Jenkin, & Zikovitz, 2000; Lamontagne et al., 2007). OF provides individuals the ability

to dynamically discern potential actions during motion, which allows for the

accommodation of obstacles within their environment. The interpretation of OF provides

the brain with another input mechanism which is then utilized to adjust gait speed and

direction of movement. Proprioception, or the body's sense of where the joints are in

space (feeling the ground beneath for instance), is closely linked with both balance and

gait function. OF provides continuous intrinsic feedback to the cerebral cortex and

brainstem that is incorporated into the vestibular system and efferent motor control

during gait (Prokop, Schubert, & Berger, 1997; Pailhous, Ferrandez, Flückiger, &

Baumberger, 1990). In healthy individuals, afferent visual and proprioceptive input are

often in accordance with one another (Harris, Jenkin, & Zikovitz, 2000). Studies have

shown that healthy participants reduced gait speed with an artificially high OF, and

increased gait speed with an artificially low OF (Prokop, Schubert, & Berger, 1997;

Pailhous et al., 1990). Mismatches between proprioceptive feedback and OF are

compensated for by alterations to gait speed, in an attempt to balance the two sources of

sensory input and achieve a form of sensory feedback equilibrium. OF relies heavily on

peripheral vision, which is often hindered in individuals following a CVA (Striemer et


al., 2007), but is a vital aspect of the neuromuscular feedback mechanism involved in

proper gait function (Lamontagne et al,, 2007; Prokop, Schubert, & Berger, 1997; Patla,

1998). Loss of peripheral vision post-CVA poses a non-motor complication to gait, since

visual interpretation of motion within the environment, is vital to safe and efficient

ambulation (Prokop, Schubert, & Berger, 1997). Visual deficits as a result of CVA have

a profound effect on the interpretation and integration of OF (von Schroeder, Coutts,

Lyden, Billings, & Nickel, 1995), and numerous studies have pointed out the benefits of

controlling optic flow during gait training (Kang et al., 2012; Lamontagne, Fung,

McFadyen, & Faubert, 2007; Pailhous et al., 1990). Standard treadmill training removes

the component of OF, since the visual field remains static. The net effect of

incorporating OF with treadmill training shows great promise (Kang et al., 2012), and

furthering research in this field may yield an innovative approach for clinical

rehabilitation following CVAs.

Kang and colleagues (2012) studied the effects of optic flow modulation via head-

mounted virtual reality device, coupled with treadmill gait training on 30 participants

affected by CVAs. The participants were randomly divided into three groups (10

participants in each): optic flow with treadmill training, a standard treadmill group, and a

control group. The researchers found that functional reach test and timed up-and-go test

results were both significantly higher in the OF group, when compared to standard

treadmill trained and control groups. Six-minute walk test (6MWT) results also showed

significantly higher improvements in distance covered versus an initial 6MWT

assessment. Increases for the OF group averaged 24.49 (±11.00) meters, while the

standard treadmill and control groups averaged increases of 4.65 (±3.25) meters and 1.79


(±3.08) meters respectively. Ultimately, the researchers concluded that modifying

treadmill training by incorporating optic flow improved gait and balance in participants

affected by CVAs.

There has been success with the utilization of VR in treating a variety of both

upper and lower extremity deficits in participants that have suffered a CVA, Parkinson’s

disease, and orthopedic injuries (specifically to the ankle). One case study utilized VR in

three participants in the chronic phase of a CVA to address upper limb movement speed,

range of motion, force production, and fractionation. A computer monitor displayed

games while the participants completed the exercises using a CyberGlove and force

feedback glove. Two of the three participants had increases in the Jebsen Test for Hand

Function score, indicating that VR may be successful in rehabilitating participants

affected by CVAs (Merians et al., 2002).

Gait biomechanics have also been improved successfully with the application of a

VR apparatus. One study involved four subjects with ankle injuries performing seated

exercises using a Rutgers Ankle Rehabilitation System (RARS) which consisted of a

haptic platform that supplies forces to the participant’s foot and a monitor displaying

virtual environments with varying exercises. There was increased range of motion,

increased self-selected walking speed, and increased ankle power push off (Girone,

Burdea, Bouzit, Popescu, & Deutsch, 2000). These improvements came from increased

ankle motor control as opposed to actual gait training. Theories of motor learning suggest

that more specific task training would result in increased learning (Winstein et al., 2004).

The effect of virtual reality on gait has also been researched in participants with

Parkinson’s Disease. One study involved having subjects wear glasses that display a


virtual checkered tiled floor. This study compared traditional open loop feedback that is

typically provided by therapists with closed loop sensory motor feedback from VR

systems in 14 Parkinson’s disease patients. The study found that closed loop systems

were superior. Whereas 13.8% of subjects improved their walking speed and 15%

improved their stride length in the open loop system, 25.7% improved their walking

speed and 30.8% improved their stride length in the virtual reality/closed loop system.

Furthermore, no participants experienced freezing of gait with the virtual reality system

(Barami, Aharon-Peretz, Simionovici, & Roni, 2003).

Studies have also addressed improving gait in individuals after a CVA. One study

used real world video recording scenarios while training on a treadmill and found greater

improvements in balance and gait time than traditional treadmill training as measured by

the Berg Balance Scale, the Timed Up and Go, postural sway calculated by a force

platform system, and a pressure walkway (Cho & Lee 2013). While this study did not

research virtual reality directly it did utilize real world scenarios that would provide optic

flow like VR systems. The use of virtual reality has also been found to be motivational to

subjects who are one year post CVA. The VR employs concepts of motor learning such

as repetitive practice in an environment. Six subjects training with VR on a treadmill and

partial body weight support (PBWS) showed functional progression in walking as

measured by the FGA, balance improvements as measured by the Berg Balance test, and

were able to increase walking speed and duration (Walker et al., 2010). Another study

using VR in 12 subjects showed improvements in community ambulation when

compared to a control group. These successes included improved walking speed,


community walking time, and Walking Ability Questionnaire score (Yang, Tsai, Chuang,

Sung, & Wang, 2008).

A Cochrane review on the use of VR for CVA rehabilitation has found statistical

significance in upper limb functioning, but no statistical significance on gait speed based

on 37 studies. Most studies reviewed had small sample sizes and the control intervention

varied greatly between them (Laver, George, Thomas, Deutsch, & Crotty, 2015).

However, studies on community walking indicate that positive research outcomes such as

increased gait speed do not always translate to functional community walking (Lord,

McPherson, McNaughton, Rochester, & Weatherall, 2004). Instead, functional outcome

measures may be more reliable in assessing progress and success in gait training. The

Functional Gait Assessment (FGA) has been proven to be a reliable and valid test

measure that gives the therapist more information regarding functional abilities rather

than tests that measure just speed or distance such as the six, or ten-minute walk test, and

had the lowest floor and ceiling effects versus the DGI and DGI-4 (Lin, Hsu, Hsu, Wu, &

Hsieh, 2010). The FGA assesses gait on a level surface, change in gait speed, gait with

horizontal head turns, gait with vertical head turns, gait and pivot turns, step over

obstacle, gait with narrow base of support, gait with eyes closed, ambulating backwards,

and steps. When comparing the FGA to the test it was initially developed from, the

Dynamic Gait Index (DGI) or its abbreviated form the four item DGI (DGI-4), the FGA

was found to be the most discriminative test for participants affected by CVA with higher

ambulation capabilities (Lin, Hsu, Hsu, Wu, & Hsieh, 2010).

The existing literature indicates that there is potential for the use of VR in CVA

rehabilitation, however small sample sizes and small statistical significance indicate a


need for further research. Furthermore, the lack of carry over to community walking

requires a better motor learning environment. Research regarding VR-based treadmill

gait training will aid in expanding the knowledge base surrounding new and innovative

gait training technologies, and may provide some insight into improving current

treadmill-based gait training strategies.

The researchers posed the following research question: To what extent does

dynamic environment training utilizing a treadmill and virtual reality (VR) environments

improve gait function in a participant with chronic neurological impairments as a result

of a cerebrovascular accident (CVA)? The researchers hypothesize that VR-based

environments designed to challenge and incorporate optic flow, used with treadmill

training, will yield neuromuscular improvements in walking in a participant with chronic

neurological impairments resulting from a CVA.

Methods

Inclusion criteria for the study included having a CVA at least six months ago

(chronic), having participated in physical rehabilitation after the episode, and must be

able to ambulate fully weight-bearing. Exclusion criteria included individuals with

osteoporosis, amputations, peripheral neuropathy, more than one prior CVA, or another

neurologic comorbidity. Participants with pre-existing orthopedic surgeries involving the

hip, knee, ankle, or foot joints from which they have not fully recovered were excluded

from the study. Dr. Mollie Venglar assisted in recruiting one participant who is greater

than or equal to six months post-CVA (chronic).

Initially, the participant went through a two-week training period made up of two

sessions the first week and one session the second week to become acquainted with the


concept of VR and the treadmill. Functional mobility was assessed via the FGA, the

6MWT, and the Qualisys motion capture system at baseline (an average of the first three

initial assessments). Next the participant went through eight weeks of gait training

sessions, two times a week. At every fourth gait training session--which equated to every

two weeks functional mobility was re-assessed. Carry over assessments were conducted

at both two and four weeks post-study. No assistive devices or orthotics were utilized at

any point during either gait training or assessment. The same two researchers conducted

and scored each Functional Gait Assessment, and an identical sequence of tasks was

adhered to, as outlined by the FGA itself, to maximize consistency between assessments.

At the beginning of each session, heart rate and oxygen saturation levels were

measured, using a finger-mounted pulse oximeter (Figure 1), to ensure participant safety.

Next, reflective markers (Figure 2) on the joints of the pelvis and legs were placed by the

researchers to track motion of the limbs while walking. Reflective markers were placed

bilaterally on the following anatomic locations: first and fifth metatarsals of the feet,

calcaneus, medial and lateral malleolus, medial and lateral epicondyles of the tibia,

anterior and posterior iliac spine, and greater trochanter. The markers were placed on the

shoes and the clothing of the participant. Qualisys Motion Capture (Figure 3) data (step

length, stride length, and cadence) were collected over three 10 meter walk trials within

the research lab.

Outcome measure testing was conducted starting with the FGA and followed by

the 6MWT. The three initial FGAs were averaged together to establish a baseline

measure for future comparative purposes. Following the FGA, a 6MWT was

administered and distance covered over the span of six minutes was recorded. The last 15


minutes of the initial assessment sessions were spent acclimating the participant to the

VR headset (Figure 4) and treadmill. An Oculus Rift VR headset was integrated with a

VR environment designed for incorporating optic flow challenges into the virtual gait

training environments. Unity 3D was utilized by FGCU bioengineering students for

designing the virtual environment. Students from Florida Gulf Coast University's

Department of Bioengineering and Software Engineering assisted the researchers in

software design and hardware setup and integration.

The speed of the treadmill was sent via an Arduino microcontroller to the VR

environment, to update the position of the participant’s avatar so that their avatar’s speed

was equivalent to the treadmill’s speed. The Oculus display uses a series of inertial

measurement units and markers to monitor its orientation, allowing the participant to

control the direction of the camera in the virtual environment

Following the three initial assessment sessions, the participant went through 16

gait training session over the span of 8 weeks with 2 sessions per week. The aim of the

gait training sessions was to progress the participant to continuous ambulation for 30

minutes, based on American College of Sports Medicine (ACSM) recommendations for

duration of exercise (ACSM, 2011). The training session frequency was chosen to

simulate a typical outpatient physical therapy program. The participant was placed inside

a safety harness while on the treadmill to prevent falls. As the participant progressed the

VR environments were modified as was the treadmill speed. Every two weeks (every

fourth session), at the beginning of the session prior to gait training, the FGA test was re-

administered in order to monitor progress followed by the 6MWT, and finally the

Qualisys Motion Capture System data collection. .


Gait training sessions and data collection was led by two Doctor of Physical

Therapy students from Florida Gulf Coast University (FGCU), under the supervision of

Dr. Mollie Venglar. Two Doctor of Physical Therapy students provided manual

facilitation to the hemiparetic limb to normalize the participant’s gait mechanic.

Subjective feedback on the VR and treadmill training and qualitative date regarding the

participant’s gait mechanics will be recorded throughout.

Figure 1: Pulse oximeter

Figure 2: Qualisys Motion Reflective

Biomarkers

Figure 3: Qualisys Motion Capture System (in use with biomarkers placed)

Figure 4: Oculus Rift CVI virtual reality

headset


Data Analysis

Results of the VR Treadmill gait training were interpreted using descriptive and

parametric statistics. The mean value of each of the outcome measures (FGA, 6MWT,

Qualisys data) obtained at the three initial assessments were compared to four subsequent

FGA assessment values (taken every 2 weeks, or every 4 sessions, during study).

Qualisys Motion Capture system data measured included stride length, step length, and

ankle ROM. Three initial assessment data points were obtained and the mean was

obtained to determine a baseline value that would take into account any potential minute

changes day to day. This comparison was in the form of line graphs with the coefficient

of determination or R2. The square root of coefficient of determination was then

calculated to obtain the Pearson Correlation Coefficient. Considering all the trend lines

were positively sloped, there was no concern with doing this. With a 1 tailed hypothesis,

95% CI, and 6 degrees of freedom derived from 7 data sets, a statistically significant r

was found to be 0.729. All Pearson Correlation Coefficients were then compared to this r

value to determine statistical significance. Percentage differences were also calculated

between the initial and final assessments to determine any changes. Pre- and post-

intervention FGA & 6MWT assessment values were calculated for minimum detectable

change (MDC), a measure of true performance change, using the standard error measure.

Results

Functional Gait Analysis

The participant consistently demonstrated improved FGA scores, with only a one-

point decrease between the first and second follow-up assessments, a non-statistically

significant change as demonstrated by Figure 5. The participant’s initial score on the


FGA was 8 and it increased 12 points to 20 by the first follow up assessment resulting in

a 150% increase indicating significant improvement in functional gait, obstacle

negotiation, and stair negotiation. A 4.2-point change is the MDC for the FGA, thus a 12

point change indicates a clinically significant change. (Lin et al., 2010). Furthermore,

Lin et al. indicates that the normative score for acute and chronic CVA on the FGA at 5

months post-CVA is 12, well below our participant’s final score. The largest increase

between assessments was seen between the fourth and eighth gait training sessions, with

the FGA score increasing from a total score of 11 to 16 out of a potential maximum of 30

points, representing a 45.5% increase. Figure 6 displays a specific by task breakdown of

the participant’s performance on the FGA. There were improvements specifically in

change in gait speed, gait with horizontal head turns, gait with vertical head turns, gait

and head turn, step over obstacle, gait with narrow base of support, and ambulating

backwards. No changes were seen in gait level surface, gait with eyes closed, or steps.

The Coefficient of Determination (R2) was calculated to be 0.843, and the Pearson

Correlation Coefficient (r) was calculated to be 0.918 indicating statistical significance in

the correlation between the gait training sessions and the FGA scores.


Figure 5. Functional Gait Assessment Scores

Key: IA_Avg: average of first 3 initial assessments GT: gait training session # FUA: follow-up assessment # Figure 6. Functional Gait Assessment Scores by Task

R² = 0.844

0

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IA_AVG GT-4 GT-8 GT-12 GT-16 FUA-1 FUA-2

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Gait level surface

Change in gait speed

Gait with horizontal head turns

Gait with vertical head turns

Gait and pivot turn

Step over obstacle

Gait with narrow base of support

Gait with eyes closed

Ambulating backwards

Steps

IA_Avg

GT-4

GT-8

GT-12

GT-16

FUA-1

FUA-2


Six-Minute Walk Test

The distance ambulated during each of the assessed 6MWTs is displayed in

Figure 7. The overall trend is an increase in the participant’s distance, from 464 feet to

557 feet at the second follow-up assessment. This is a 20.0% change in distance covered.

There was an initial drop in 6MWT distance during the first two gait training data

collection sessions (GT-4 and GT-8), compared to the initial assessment average. The

participant’s distance decreased from 465ft to 381ft, and then increased to 413ft, which

remained lower than the initial average.

Not only did the participant’s 6MWT distance improve by the final intervention

session, but her distance continued to improve at the follow up visits increasing to 671ft.

This is a 207ft increase, meeting the MDC normative value of individuals post-CVA of

112.8ft (Eng, Dawson, & Chu, 2004). The increase in total distance covered throughout

6MWT assessments represents a significant improvement in both gait velocity and

endurance. The Coefficient of Determination (R2) was calculated to be 0.733, and the

Pearson Correlation Coefficient (r) was calculated to be 0.856 making it statistically

significant.


Figure 7. Six Minute Walk Test Distance

As the 6MWT is meant to be a test of cardiovascular endurance, heart rate (HR)

was measured both before and after the assessment. The HR measurements displayed in

Figure 8 show an overall decreasing trend in pre and post HR indicating that the

cardiovascular demand required of the task decreased with more intervention. This can be

seen by the decrease in pre-HR from 104 bpm to 74 bpm by the last follow-up assessment

and decline in post HR from 117 to 96 bpm. The pre-HR data did not however decline

consistently. There was an initial increase in the participant’s pre-HR compared to the

initial assessment, up until the fourth gait training session. The post-HR data declines

also showed some inconsistencies, the lowest post HR was found to be 76 at the first

follow-up assessment but was elevated during the second (final) follow-up.

R² = 0.734

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500

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800

IA_Avg GT-4 GT-8 GT-12 GT-16 FUA-1 FUA-2

Dis

tanc

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)


Figure 8. Heart Rate Pre and Post Assessment

Average velocity was calculated from the 6MWT data to assess any changes. As

Figure 9 displays, the participant’s initial average velocity was 0.393 m/s but then it

dropped by fourth gait training trial to 0.323 m/s. From that point it continued to

gradually increase except for a slight decrease at the first follow up assessment. The final

velocity was found to have increased to 0.568 m/s, demonstrating an overall increase in

velocity of 44.5% with the intervention. The Coefficient of Determination was calculated

to be 0.736 r2 and Pearson Correlation Coefficient was calculated to be 0.857 indicating a

statistically significant correlation.

020406080

100120140160180200220240260

Hea

rt R

ate

(BPM

)

HR_post (BPM)

HR_pre (BPM)


Figure 9. Average Velocity from 6MWT

Spatiotemporal Gait Parameters

Step Length. Step length of both the right and left lower extremities

demonstrated a consistently remarkable increase, as evidenced by Coefficient of

Determination R2 values of 0.766 and 0.860, respectively and correlation coefficients of

0.875 and 0.927. Left step length (the hemi-paretic limb) showed a more marked

increase relatively, as evidenced in Figure 7. Left step length data revealed a 62.5%

increase between the initial assessment average (0.24 m) and follow-up assessment 2

(0.39 m), while right step length increased 22.6% between the initial assessment average

(0.31 m) and follow-up assessment 2 (0.38 m).

Step length of the affected left lower extremity was found to be more limited than

the contralateral right lower extremity (0.24 meters on the left compared to 0.31 on the

right). With increased intervention however, the left step length increased to 0.39 meters

and the right step length increased to 0.38 meters. By the final follow up assessment

there was only a 0.01 meter difference between the bilateral step lengths resulting in a

much more equal gait pattern. Regression lines were calculated for both charts and both


were found to be highly statistically significant for a correlation between intervention

session and increase in step length.

The researchers’ primary focus throughout the gait training sessions was on the

normalization of the participant’s gait mechanics, by emphasizing increased hip flexion

of the left lower extremity through initial and mid-swing, improved eccentric control of

knee extension through terminal swing, minimization of left foot inversion throughout the

swing phase of gait, with an emphasis on improving heel strike at initial contact in order

to facilitate a more normalized heel-to-toe progression of the hemi-paretic foot. The

researchers’ primary aim with normalization of gait mechanics was to improve both

efficiency and fluidity of gait, which was assessed by both cadence and distance covered

during the 6MWT. Qualisys Motion Capture System data provided a series of data

relative to right and left step length, as well as stride length and cadence. This is

displayed in Figure 10.

The participant demonstrated a consistent increase in both right and left step

lengths throughout the course of the study, with a more marked increase between initial

assessment average and follow-up 2 data evident in the left lower extremity (62.5%), than

the right lower extremity (22.6%). The improvements in both right and left step length

were remarkably steady and consistent, as evidenced by R2 values of 0.766 and 0.860 for

right and step length data respectively, show in Figure 11.


Figure 10. Qualisys Spatiotemporal Gait Paramaters

Session L_StepLength

(m) R_StepLength

(m) Stride Length

(m) Cadence

(steps/min) IA_Avg 0.24 0.31 0.54 77.82 GT-4 0.27 0.30 0.57 79.07 GT-8 0.25 0.31 0.57 68.81 GT-12 0.26 0.32 0.58 75.64 GT-16 0.33 0.34 0.67 79.46 FUA-1 0.31 0.35 0.66 80.93 FUA-2 0.39 0.38 0.77 79.29

Figure 11. Right and Left Step Length

Likewise, stride length also demonstrated significant improvement over the

course of the study as demonstrated by Figure 12. At initial assessment stride length was

found to be 0.54 meters and it increased consistently until by the final follow up to 0.77

meters. The Coefficient of Determination was calculated to be an R2 value of 0.849 and

Pearson Correlation Coefficient r was calculated to be 0.921 which indicates a strong

statistically significant correlation between intervention and stride length.

R² = 0.766

R² = 0.860

0.20

0.25

0.30

0.35

0.40

Step

Len

gth

(met

ers)

L_StepLength R_StepLength

Linear (L_StepLength) Linear (R_StepLength)


Figure 12. Stride Length

Cadence. Cadence, calculated as steps per minute, was found to increase from

77.82 to 80.93 at the first follow up assessment and back down to 79.29. This is

displayed in Figure 13. There is a significant outlier at gait training session 8 where the

cadence dropped to 68.81 steps per minute. This outlier throws off the regression line

and resulted in a very low Coefficient of Determination (R2 = 0.126 ) and Pearson

Coefficient of determination (r = 0.353) indicating a poor correlation.

Figure 13. Cadence

R² = 0.850

0.500.550.600.650.700.750.80

Met

ers

Session

R² = 0.126

666870727476788082

IA-AVG GT-4 GT-8 GT-12 GT-16 FUA-1 FUA-2

Cad

ence

(ste

ps/m

inut

e)

Session


Discussion

Functional Gait Assessment

Despite the 150% improvement in the FGA from initial assessment, the

performance of the participant in this study brings to light potential limitations of the

FGA. Many subjective improvements were noted, however, these were not reflected

quantitatively. For example, the researchers noted less pronounced time over the non-

affected lower extremity during the gait over level surfaces task, as well as significant

improvement in the time required to ambulate the standard 20 feet, from 15.8 seconds at

initial assessment to 12.7 seconds at the second follow-up assessment. The participant

experienced a "ceiling effect" in this particular category due to a time constraint of 7

seconds or less, in order to receive a score of two out of three points in the gait over level

surfaces category. Similarly, gains observed by the researchers with regard to stair

negotiation were not reflected in FGA score improvements for the particular task.

Significant improvement in reciprocal stepping was demonstrated throughout the study,

as well as improved eccentric knee control of the hemi-paretic lower extremity during

descent of stairs. The FGA score for the steps category remained at two out of three

potential points due to the use of a single handrail on the non-paretic side.

The FGA did however accurately capture improvements in backwards

ambulation, as measured by a consistently held one-point increase from the fourth gait

training session onward. The researchers subjectively noted improved quality of stepping

and toe-to-heel progression, as well as a decrease in time to complete task throughout all

of the gait training sessions and both follow-up assessments. Ultimately, time restrictions

imposed by the FGA, and the inability to capture improvements relative to reduced fall


risk and improved single-leg balance limited the ability of the FGA to capture subjective

gains, but ultimately the researchers concluded that the FGA fairly and accurately

represented functional gains achieved throughout the study. The results from this study

are comparable to the only other VR that analyzed the FGA as both demonstrated

improvements with our study demonstrating greater improvements (Walker et al., 2010).

Six-Minute Walk Test

The participant was able to meet the MCD index change and showed great

improvement in 6MWT distance covered, velocity, and gait quality. The participant’s

initial decrease following the initial assessments may be explained by the emphasis on

gait quality as opposed to speed and also by the fact that the participant reported having a

flu and was forced to miss one of the gait training sessions for as a result. Pre- and post-

HR data, as well as the 6MWT score increases indicate improvement in cardiovascular

endurance, but analysis of the gait during the walk also indicated improved ankle

dorsiflexion and eversion. The overall decreasing trend in pre- and post-HR also prove

the improvements in cardiovascular endurance. The endurance gains indicated by the

6MWT also carried over to day to day function as the participant reported improved

distance in daily walking from 0.25 miles initially to 3 miles by the completion of the

study. These differences can be explained by the amount of physical activity the patient

had performed right before the intervention sessions.

While increased gait velocity receives a lot of emphasis in the literature, research

involving individuals with a CVA indicates that velocity does not always translate to

improved community walking (Lord et al., 2004). Therefore, increasing gait speed was

not a priority for our study. Despite this however we were able to find improvements in


gait velocity as measured by the 6MWT. The participant was able to achieve a speed of

0.568 m/s during the 6MWT which is within the expected velocity post CVA of 0.30 and

0.80 meters, but does not meet the safe community ambulation speed of 0.90 m/s or the

normal walking speed of 1.2 m/s in healthy adults (Tilson et al., 2010). This is

comparable to the improvements found by Walker and colleagues (2010) in gait speed

with VR and treadmill training. However, it is important to note that despite the

researchers’ success with increased gait speed the researchers cannot conclude that the

improvements are greater than that of traditional therapy. One literature review by de

Rooik, Ilona, van de Port, and Meijer (2016) found that eight out of eleven studies

showed significant increases in gait speed in the VR group when compared to a control.

A Cochrane Review by Laver and colleagues (2015) made different conclusions. They

found that there is very low quality evidence indicating that there is no significant

difference between virtual reality and conventional therapy for walking speed. It’s

important to note that not all of the studies in the literature reviews utilized the same

virtual reality apparatus as the present study.

It is important to note that normative data for CVA is typically for a geriatric

population (65+) whereas the participant in the present study was a younger individual.

Furthermore, most of the gait velocity data in research refers to the acute stage of a CVA

not chronic like the present study’s participant.

Step-Length

The data indicates that both right and left step length improved throughout the

study. During overground walking and treadmill walking the researchers noted that the

participant was beginning to demonstrate improved dorsiflexion and eversion of the left


foot between gait training sessions, and between gait training sessions 3 through 7, the

participant was exhibiting more evident carryover of the increased dorsiflexion and

eversion control between sessions, with less manual facilitation from researchers. While

the participant exhibited signs of fatigue during the first three gait training sessions,

improved endurance to ambulation and time on treadmill became evident by the fourth

and fifth gait training sessions. By gait training session 10, the participant was able to

tolerate 17.5 minutes of continuous ambulation without rest, as compared to 5.0 minutes

of ambulation before requiring a rest break during gait training session 1. A marked

increase in eccentric left knee control was noted during the FGA performed at gait

training session 8, and was repeatedly observed throughout all remaining assessments.

Observation also revealed notable increases in endurance and average gait velocity

throughout each of the 6MWTs performed at gait training sessions 4, 8, 12, and 16, with

only a minor decrease between gait training session 16 and follow-up assessment 1 (7 ft).

At the conclusion of the study (follow-up assessment 2), researchers noted the

following general observations of the participant’s gait as compared to the initial

assessment notes: increased gait velocity, a narrower base of support, more symmetrical

step length, improved foot clearance via dorsiflexion control of the left foot, and

decreased incidence and amplitude of left knee hyperextension through terminal stance,

and improved control of left foot inversion throughout the swing phase. This all supports

the inclusion of virtual reality treadmill training into future rehabilitation of chronic post-

CVA individuals.


Cadence

There was heavy emphasis from the researchers between gait training sessions 4

and 8 on quality of stepping versus the rate (cadence) or speed (velocity) of stepping,

which may assist in understanding the reduction in cadence from 79.07 steps per minute

as assessed at gait training session 4, to 68.81 steps per minute as assessed at gait training

session 8. Focus was placed on the minimization of inversion throughout the swing

phase of gait, as well as the accurate and consistent achievement of heel strike at initial

contact with the left foot (hemi-paretic limb), with a gradual decrease in manual

facilitation occurring throughout gait training sessions 4 to 8. A gradual increase in

cadence was noted from gait training session 8 through the first follow-up assessment.

The reduction in cadence between follow-up assessments 1 and 2 was deemed to be

insignificant (1.64 steps per minute) by the researchers, representing only a 2.03%

decrease.

Limitations

Some of the limitations in our study overall include the sample size. As this is a

case study the results cannot be extrapolated to the general population. It is however a

very promising start and supports the existing research regarding the benefits of Virtual

Reality. Another potential limitation is the age of our participant. Seventy-five percent

of CVAs occur in those over the age of 65 however our participant was much younger.

This age discrepancy might influence the personal experiences and attitude towards the

virtual reality treatment and makes it difficult to compare to normative data. The final

limitation is in regards to future replication of the study. The treadmill and virtual

environments being utilized were all designed by engineering students at FGCU.


Participant Feedback

Oral interview and subjective feedback from the participant gave the researchers

insight on the participant satisfaction of using VR. The participant expressed that it is an

intervention she would feel encouraged and motivated to participate in. She did not

experience any adverse reactions to the virtual reality (no dizziness, vertigo, nausea was

reported during any of the assessment or gait training sessions). The only major

complaint was in regards to the VR goggles and how hot they made her face feel. This

problem was quickly resolved by adding a fan in front of the treadmill. Another

subjective negative is the participant’s feeling that not all gains were 100% translatable to

land ambulation. Recommendations from the participant were primarily regarding the

saliency of the environments. Initially the environment was a nature train with mountains

and trees and while it was aesthetically pleasing and enjoyable it wasn’t translatable to

the participant’s personal environment in Florida. As one of the main reasons for

utilizing VR is the optic flow feedback this is a very notable recommendation. When the

environment was changed to a downtown city environment that is relatable to the

participant her satisfaction increased. Future research is needed with a greater sample

size and with an omnidirectional treadmill to enhance the optic flow and realistic

experience of the participant.

It is not possible to determine from our study whether VR is more beneficial than

conventional treadmill training without virtual reality. However, it is clear that VR has its

benefits and that further studies with greater sample sizes and controls may help answer

that question. Even if future studies find that it is not more beneficial than treadmill or

over-ground training but is equally beneficial there is still value in VR. Further cost


analysis and comparative motivation to participate and overall participant satisfaction

research would be needed to determine if the high cost of VR is indeed worth integrating

it clinically.

Conclusion

Combining VR with treadmill training post-CVA appears to be a feasible

intervention strategy for clinical rehabilitation purposes. The researchers maintain that

the incorporation of optic flow during treadmill-assisted gait training yields significant

improvement in over ground ambulation carryover relative to observations measured by

the 6MWT, FGA, and Qualisys Motion Capture System data. Improvements were noted

in quantitative and qualitative aspects of gait during the study and maintained at follow-

up.

This single-participant case study was intended to assess the feasibility of

incorporating VR with treadmill training post-CVA. The novelty of the combined

intervention coupled with both promising results as well as the long-term retention of the

noted improvements reveals a strategy with real-world clinical promise. The researchers

believe that the positive results obtained from this study indicate a strong need for further

research incorporating VR with treadmill training over larger participant groups, and

more comparative studies with appropriate control groups.


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Appendix: Virtual Reality Environments

Figure A1: VRForest

Figure A2: River Run

Figure A3: Color Forest

Figure A4: TCity

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