Clinical, Functional and Kinematic Correlations using the Virtual

Reality System Toyra® as Upper Limb Rehabilitation Tool in People

with Spinal Cord Injury

Iris Dimbwadyo-Terrer

, Fernando Trincado-Alonso

, Ana de los Reyes-Guzmán

Alberto Bernal-Sahún

, Patricia López-Monteagudo

, Begoña Polonio-López

and Ángel Gil-Agudo

Biomechanics and Technical Aids Department, National Hospital for Spinal Cord Injury,

Finca la Peraleda s/n, Toledo, Spain

Indra Systems, Madrid, Spain

University of Castilla la Mancha, Talavera de la Reina, Spain

Keywords: Upper Limb, Rehabilitation, Spinal Cord Injury, Toyra, Virtual Reality.

Abstract: The aim of this study was to prove the validity and efficacy of the Virtual Reality (VR) System Toyra® as

an assessment and rehabilitation tool for people with tetraplegia. We analysed the correlation between

clinical and functional parameters with kinematic variables of upper limbs during a training protocol using

Toyra®. Eighteen patients with cervical spinal cord injury (SCI) were selected to perform the study by

comparing 2 treatments: patients in an intervention group (IG) conducted a program that included 12

sessions with Toyra® Activities of Daily Living (ADLs) module for 3 weeks, while a control group (CG)

only had the traditional rehabilitation. Kinematic variables (shoulder, elbow and hand joint range of motion)

were correlated to clinical [Motor Index (MI), Muscle Balance (MB)] and functional [Functional

Independence Measure (FIM), Spinal Cord Independence Measure II (SCIM II), Barthel Index (BI)]

evaluation scores. The results of the study showed a high correlation between these variables and also

statistically significant differences (p=0.039) in a kinematic parameter (wrist extension), after treatment and

in the follow-up evaluation. Toyra® system has been validated as upper limb assess and rehabilitation tool

in people with SCI, to measure the patient´s functional evolution and improve the movement in upper limbs.

1 INTRODUCTION

The worldwide estimate of the prevalence of spinal

cord injury (SCI) is 223-755 per million people, with

an incidence of 10.4-83 per million individuals per

year

(Wyndaele and Wyndaelem, 2006). Fifty

percent of the patients with SCI are diagnosed as

complete, with one-third of them reported as

tetraplegic.

In tetraplegia, the arm and hand function is

affected to varying degrees, depending on the level

and severity of the injury (Harvey et al., 2001).

Studies have shown that one of the greatest needs

of patients with tetraplegia is the improvement in

upper limb function

(Snoek et al., 2004).

In this respect, therapy aimed at upper

extremities in people with tetraplegia is of

paramount importance.

Considerable efforts have been directed towards

the development of new upper limb (UL) function

rehabilitation therapies using robots, virtual reality

(VR), passive workstations (passive antigravity

orthosis), and functional electrical stimulation (FES)

systems

(Oess et al., 2012).

Specifically, in an effort to promote task oriented

and repetitive movement training of motor skills the

use of VR with simulated environments has emerged

as a useful tool

(Stewart et al., 2007).

Using VR, users are able to interact with images,

manipulate virtual objects, and perform other actions

in a way that allows them to “immerse” themselves

within the simulated environment and thereby create

a feeling of “presence” in the virtual world

(Weiss et

al., 2006). In comparison with conventional

rehabilitation, VR technology increases the range of

possible tasks, while partly automating and

quantifying therapy procedures, and improving

patient motivation using real-time task evaluation

and reward

(Eng et al., 2007).

Dimbwadyo-Terrer I., Trincado-Alonso F., de los Reyes-Guzmán A., Bernal-Sahún A., López-Monteagudo P., Polonio-López B. and Gil-Agudo Á..

Clinical, Functional and Kinematic Correlations using the Virtual Reality System Toyra

 as Upper Limb Rehabilitation Tool in People with Spinal Cord

Injury.

DOI: 10.5220/0004642600810088

In Proceedings of the International Congress on Neurotechnology, Electronics and Informatics (VirtRehab-2013), pages 81-88

ISBN: 978-989-8565-80-8

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

To measure the effectiveness of such techniques,

an evaluation, using clinical and functional scales, is

performed before and after the treatment program to

identify motor and functional recovery. In evaluation

studies of upper extremity function in people with

tetraplegia, a functional test supplemented with a

test in which the subject is asked to perform several

activities of daily living (ADL) are used

(Van Tuijl

et al., 2002). Two of the most commonly used

functional evaluations, for patients with tetraplegia,

are the Functional Independence Measure (FIM) and

the Spinal Cord Independence Measure II (SCIM II).

There tests are valid and reliable, and show strong

correlation with each other.

However, a better understanding of human

movement requires more objective testing and

accurate analysis of motion, to accurately describe

the arm movements during functional activities.

Kinematic analysis is one method that can provide

this understanding

(Alt Murphy et al., 2006).

The study carried out by Cacho et al. (2011)

showed correlation between some kinematic

variables and clinical measures, in people with SCI,

during the execution of ADLs

(Cacho et al., 2011).

The objective of the current study is to analyse

the correlation between clinical and functional

assessments and the kinematic variables of UL. This

is performed by comparing the results from a

treatment based on VR with those from a

conventional rehabilitation treatment in patients with

complete tetraplegia.

2. MATERIAL AND METHODS

2.1 Participants

Twelve intervention subjects (4 females and 8

males; aged 33.58±14.11 years, 3.67±1.78 months

after injury) and 6 control subjects (3 females and 3

males, aged 42±13.56 years, 6.67±2.16 months after

injury) participated in the study. The subjects’

demographic and clinical characteristics are showed

in the Table 1.

Eligible participants met the following criteria:

(1) at least 18 years of age; (2) less than 12 months

from the injury; (3) complete spinal cord injury

according to the ASIA´s impairment scale at the

level of C5 to C8 (A-B ASIA level); (4) no history

of traumatic or cognitive pathology that can affect

the UL movements; (5) normal or corrected-to-

normal vision and hearing; (6) no history of

technology addiction; and (7) no history of epilepsy

and pregnancy. Each subject gave informed consent

voluntarily which was approved by our local Ethics

Committee.

Table 1: Subjects´ demographic and clinical characteristics

(mean and standard deviation).

Control Group

(n=6)

Intervention Group

(n=12)

Gender

(female/male)

3/3 4/8

Age [years]

42±13.56 33.58±14.11

Dominance

(right/left)

3/3 5/7

Level of injury

(C5-C8)

C5 (4), C6 (1) ,

C7 (1)

C5 (5), C6 (3), C7 (3),

C8 (1)

ASIA (A-D)

A(3),B(3) A(8), B(4)

Time since injury

[months]

6.67±2.16 3.67±1.78

Etiology of damage

(traumatic/postsurgi

cal/vascular)

6/0/0 11/1/0

2.2 Experimental Design

This is a research study comparing 2 treatments.

Patients in intervention group (IG) took part in a

treatment program that included 12 sessions with

Toyra® ADLs module using 3 levels of difficulty

for 3 weeks. Simultaneously to Toyra® treatment,

patients also received a daily session of conventional

Occupational Therapy and Physiotherapy. Patients

assigned to the control group (CG) only had the

conventional treatment without receiving the

described Toyra® sessions.

Figure 1: Experimental Design. The flowchart represents

the experimental design followed during the study.

NEUROTECHNIX2013-InternationalCongressonNeurotechnology,ElectronicsandInformatics

Every subject (CG and IG) was evaluated twice:

at the beginning of the study and at the end, using

both the VR system and the clinical and functional

scales. A small sample from each group was

followed up and assessed 3 months after the study,

to measure if there were kinematic, functional or

clinical changes during this period (Figure 1).

In order to prove the validity of the VR system

Toyra® as an assessing tool, we correlated clinical

and functional evaluations with kinematic variables

of UL movements in patients with tetraplegia at

three different points: before and after the treatment,

and 3 months later (follow-up).

2.3 Treatment

The treatment system used was the VR Toyra®,

which was comprised of motion capture elements

that reproduce, in real time, the movements of the

patient through an avatar displayed on an LCD

screen, the characteristics of the system having been

described previously

(Gil-Agudo et al., 2012). A

series of objects are shown, and the avatar, which

represents the patient, has to touch them, while

following predefined treatment goals.

In the current study we have conducted one type

of interactive therapy session with the Toyra®

system:

- Activities of Daily Living (ADLs) Session: The

main objective is to achieve the maximum degree of

autonomy that is possible while performing ADLs

training in the VR system. In this session the

monitor displayed several objects (spoon, fork,

comb, sponge), asking the patient to reproduce the

movements necessary to perform the corresponding

ADL activities (eating with spoon, eat with a fork,

combing hair and wash your face with a sponge).

2.4 Assessment

For the kinematic capture process we used a motion

capture system based on inertial sensors MTx Xsens

Company (Xsens Ic, Netherlands) which comprised

of a gyroscope, an accelerometer and a

magnetometer, which allowed us to know the

position in Cartesian space. For this application we

used 5 inertial sensors located on the head, trunk,

arm, forearm and hand. The captured inertial sensor

data and UL anthropometric data was used to

develop a biomechanical model that has been

previously reported (Gil-Agudo et al., 2011).

The kinematic assessment protocol consists of

the performing of one test, The Evaluation Session,

described as follows:

- Evaluation Session: The principal objective is to

assess the patient's functional capacity. This is

carried out by recording the kinematic variables for

the different degrees of freedom during the

execution of analytical movements of the UL. The

ranges of motion (ROM) of the shoulder, elbow and

wrist joints were analysed with MATLAB

(MATLAB R2009a, 2009), a mathematics software

tool.

Neurological examinations of all the patients were

performed according to the ASIA standards (Marino,

et al., 2003). The right and left motor indexes were

determined from the sum of the muscle strength

(MB) of C5 and T1 segments from right and left

extremities, respectively. For each motor index,

scores ranged from 0 to 25.

The functional examination was carried out

using four scales. FIM consists of 18 items

organized into six categories, four corresponding to

motor functions (self-care items, sphincter control,

mobility items, and locomotion) and two

corresponding to cognitive functions

(communication, psychosocial, and cognitive). The

lowest and highest scores of the total ranged from 18

to 126 (Hamilton et al., 1991). The second scale was

SCIM II that has 16 items divided into three

functional areas: self-care, respiration and sphincter

management, and mobility. Total score can vary

from 0 (minimal) to 100 (maximal) (Catz et al.,

1997). The Barthel Index (BI) consists of 10 tasks:

eating, bathing, grooming, dressing, bowels, bladder,

toilet use, transfers (bed to chair and back), mobility

(on level surfaces) and stairs. Total score is from 0

to 100 (Mahoney and Barthel, 1965.). The fourth

assessment scale was the UL part of Motor Index

(MI) that assesses the power and range of active

movement, which are rated for shoulder abduction,

elbow flexion, and pinch between the thumb and

index finger. Each movement is rated on a 0-100

point scale

(Demeurisse et al., 1980).

2.5 Data Analysis

The Pearson correlation coefficient was used to

correlate kinematic variables (shoulder, elbow and

wrist ROM) with clinical and functional variables. A

significance level of p less than 0.05 was used. To

compare the mean values of the kinematics, clinical

and functional variables between groups, the

nonparametric Mann-Whitney test was used. The

statistical analysis was done with the program SPSS

17.0

Clinical,FunctionalandKinematicCorrelationsusingtheVirtualRealitySystemToyra®asUpperLimbRehabilitation

ToolinPeoplewithSpinalCordInjury

3 RESULTS

Since no differences were found in any of the

analyzed variables, obtained from the first

assessment session using the Toyra® system and the

battery of scales, we conclude that the initial

functional status was similar between the groups.

When comparing the kinematic data, obtained

from the Toyra®, of both groups after treatment we

found a statistically significant difference (p=0.039)

in the wrist extension ROM. No statistically

significant difference was obtained in any of the

clinical and functional variables. However, notable

differences, more than one point between the groups,

were found when the pre and post evaluations were

compared using the parameters for BI and MI

dominant arm, showing higher scores for the IG.

Furthermore, for most of the items in the follow-up

evaluation (3 of the 5 items) and the ´follow-up

after´, obtained from the subtraction of the ´after´

from the ´follow-up´, (4 of the 4 items) patients from

the IG presented larger scores than those from the

CG (Tables 2 and 3).

Positive correlations between clinical and

functional measures and the kinematic variables

were found in the CG before treatment: FIM and

elbow flexion complete (r=0.966, p=0.034), MB and

elbow flexion complete (r=0.971, p=0.029), MI and

elbow flexion complete (r=0.999, p=0.001); after

treatment: MI and elbow extension (r=0.995,

p=0.005);and in the follow up evaluation: SCIM and

elbow extension (r= 0.998, p=0.041), MB and wrist

supination (r=0.999, p=0.024).

In relation to the IG we also found positive

correlations between clinical and functional

measures and the kinematic variables before

treatment: MB and wrist extension (r=0.642,

p=0.045), MB and wrist ulnar deviation

(r=0.654,p=0.040), MI and shoulder abduction by

steps (r=0.610, p=0.046), BI and shoulder flexion by

steps (r=0.618, p=0.043), BI and wrist extension

(r=0.611, p= 0.046); after treatment: MB and wrist

pronation (r=0.649, p=0.031), FIM and wrist

pronation (r=0.747, p=0.013); and in the follow up

evaluation: SCIM and elbow flexion by steps

(r=0.808, p=0.028).

Negative correlation in the IG between FIM and

wrist extension after treatment (r=-0.665, p=0.036)

were obtained in the IG. The results are shown in

Table 4.

Table 2: Clinical and functional parameters in both groups before and after treatment program. The table shows the results

of each group (mean and standard deviation) and the differences between groups (p) in different stages of the protocol. The

parameter “Follow up – After” is obtained by subtracting "after treatment" from "follow-up". *Statistically significant

differences.

Before treatment After treatment

CG IG p CG IG P

SCIM [0-100]

25±9.6 24.42±7.24

0.851

29.83±6.17 27.75±4.91

0.605

FIM [18-126]

63±4.76 60.20±5.86

0.395

65.00±6.68 61.80±4.36

0.395

BI [0-100]

19.17±12.81 17.92±13.39

0.813

23.33±16.02 23.75±12.27

0.668

MB DOMINANT ARM

[0-25]

12±6.35 14.09±5.99

0.511

13.83±6.91 14.82±5.67

0.646

MI DOMINANT ARM

[0-100]

71±15.01 66.33±13.95

0.639

78.33±20.08 75.50±15.16

0.572

Follow-up Follow up – After

CG IG p CG IG P

SCIM [0-100]

26.00±4.58 36.29±8.75

0.052

-2.00±2.64 7.57±9.91

0.086

FIM [18-126]

59.67±3.51 65.57±6.87

0.203

-2.33±4.04 4.43±3.99

0.067

BI [0-100]

29.50±2.88 27.86±8.59

0.246

-3.33±2.88 -0.71±6.72

0.410

MB DOMINANT ARM

[0-25]

13.33±7.76 13.43±5.19

1.00

0.33±2.30 0.14±1.67

1.00

MI DOMINANT ARM

[0-100]

79.67±24.13 79.29±14.24

0.817

2.67±4.61 2.71±12.61

1.00

NEUROTECHNIX2013-InternationalCongressonNeurotechnology,ElectronicsandInformatics

Table 3: Kinematic variables in both groups before and after treatment program. The table shows the ROM results in each

group (mean and standard deviation) and the differences between groups (p) in different protocol stages.

Before treatment

CG IG p

abdshoulder_s

90.56±39.10 88.92±37.73

0.896

abdshoulder_c

93.67±34.49 101.46±45.63

0.896

fshoulder_s

139.96±63.84 133.70±47.91

0.794

fshoulder_c

130.32±60.73 129.21±41

1.000

felbow_s

129.69±15.04 116.14±23.99

0.361

felbow_c

130.31±14.58 121.77±13.46

0.361

exelbow

137.88±23.46 136.67±20.87

0.896

rotshoulder

121.24±40.02 103.05±29

0.361

exwrist

56.35±16.60 58.12±18.57

0.433

supwrist

138.89±20.20 148.73±69.94

0.361

pronwrist

38.11±21.33 54.33±11.66

0.192

rdwrist

28.33±12.42 25.19±8.86

0.602

udwrist

20.38±14.68 31.53±11.85

0.240

After treatment

CG IG p

abdshoulder_s

99.99±40.20 99.94±38.70

0.0808

abdshoulder_c

96.57±33.10 108.86±38.47

0.544

fshoulder_s

128.46±67.56 151.73±42.96

0.396

fshoulder_c

124.94±66.02 150.64±40.99

0.544

felbow_s

141.21±13.69 127.39±28.96

0.332

felbow_c

135.21±13.97 125.39±19.21

0.275

exelbow

141.89±20.40 141.01±29.08

0.903

rotshoulder

106.17±49.24 134.81±81.54

0.467

exwrist

50.19±12.70 74.39±25.39

0.039*

supwrist

149.66±29.98 143.57±30.33

0.716

pronwrist

34.04±11.91 47.67±22.63

0.332

rdwrist

40.92±29.58 38.73±17.24

0.903

udwrist

34.53±35.28 36.30±14.78

0.396

Follow-up

CG IG p

abdshoulder_s

80.35±21.21 126.57±46.54

0.305

abdshoulder_c

79.65±21.22 121.17±41.47

0.210

fshoulder_s

114.14±67.49 161.75±25.90

0.425

fshoulder_c

109.15±64.92 151.67±21.25

0.305

felbow_s

150.19±17.46 142.65±5.70

0.425

felbow_c

141.64±17.21 134.26±18.06

0.732

exelbow

154.43±37.08 145.53±22.23

0.732

rotshoulder

165.37±114.77 143±60.93

0.909

exwrist

56.89±4.74 66.56±14.47

0.138

supwrist

133.27±23.92 177.54±80.85

0.210

pronwrist

38.09±26.18 68.90±22.13

0.138

rdwrist

27.46±10.82 57.29±49.76

0.425

udwrist

27.17±9.92 34.42±19.04

0.732

abdshoulder_s: shoulder abduction by steps; abdshulder_c: shoulder abduction complete; fshoulder_s:

shoulder flexion by steps; fshoulder_c: shoulder flexion complete; felbow_s: elbow flexion by steps;

felbow_c: elbow flexion complete; exelbow: elbow extension; rotshoulder: shoulder rotation; exwrist:

wrist extension; supwrist: wrist supination; pronwrist: wrist pronation; rdwrist: wrist radial deviation;

udwrist: wrist ulnar deviation.

Clinical,FunctionalandKinematicCorrelationsusingtheVirtualRealitySystemToyra®asUpperLimbRehabilitation

ToolinPeoplewithSpinalCordInjury

Table 4: Statistically significant differences found in the

correlation between clinical and functional variables with

kinematic variables in CG (a) and IG (b) in the different

protocol stages.

SCIM FIM MB MI

felbow_c

r:0.971

p:0.029 b

r:0.971

p:0.029 b

r:0.999

p:0.001 b

exelbow

r:0.998

p:0.041f

r:0.995

p:0.005 a

supwrist

r:0.999

p:0.024 f

a. CG correlations (r= Pearson correlation coefficient; p=

significance level). Protocol stages: b= before treatment, a=after

treatment, f=follow up.

SCIM FIM BI MB MI

abdshoulder_s

r:0.610

p:0.046b

fshoulder_s

r:0.618

p:0.043b

felbow_s

r:0.808

p:0.028

exwrist

r:0.611

p:0.046b

r:0.642

p:0.045b

prowrist

r:0.747

p:0.013a

r:0.649

p:0.031a

udwrist

r:0.654

p:0.040b

b. IG correlations (r= Pearson correlation coefficient; p=

significance level). Protocol stages: b= before treatment, a=after

treatment, f=follow up.

4 CONCLUSIONS AND FUTURE

WORK

The present study shows a work based on the

validity of the VR system Toyra®, in measuring the

changes in kinematic variables by comparing them

with clinical and functional results. We have also

measured the efficacy of this system as a

rehabilitation tool. The VR system Toyra® has

proved to be valid and consistent not only as an

assessing tool, but also as a rehabilitation device.

In a previous study

(Gil-Agudo et al., 2012), we

found trends indicating improvements in kinematic,

functional and clinical variables after treatment in

the IG. Statistically significant differences were

found between the groups from the results of a test

that assessed the manipulative skill, coordination

and fine grip. The trend obtained from the patients in

this study, where the values of the functional and

clinical upper limb parameters were increased in the

IG, corroborating the findings from the preliminary

study. Muscle strength could be a good indicator of

functional and clinical conditions of patients with

tetraplegia. Some researchers (Beninato et al., 2004),

have shown the specific contribution that each

muscle group has on the accomplishment of motor

tasks, assessed by FIM, in patients with low cervical

lesions. The positive trends found in the scales that

assess both power and range of active movements

(MI) and activities of daily living (BI), after the

ADLs training with the VR system, support these

theories.

It is important to highlight that the IG maintains

better results, in the clinical and functional scales,

than CG from the results obtained by subtracting

after treatment from follow-up. This means that

people in IG continue improving even after the

treatment, while CG patients lost most of the

improvements.

In addition, there was a statistically significant

difference between groups after treatment for the

wrist extension ROM. The Toyra® system requires

from the patient through the execution of arm and

hand activities, like eating with a spoon or combing

their hair wrist movements. Our proposed hypothesis

is that due to this training, the patients have

increased their hand dexterity.

We also think that the small sample size and the

short time of intervention with the Toyra® system

are contributing factors to the lack of statistical

significance in the others scales.

In this study, the correlations between functional

and clinical variables and kinematic parameters, in

different treatment times, were studied in order to

know the kind of relation and the system

effectiveness as measure tool.

First of all, we want to highlight that we have

found correlations in every evaluation stage and in

all the kinematic, clinical and functional variables in

both groups.

The functional scales used in this study (FIM,

SCIM and BI) showed positive correlations with the

kinematic variables and corroborate the findings of

studies that present a relationship between functional

and kinematic variables

(Tsao and Mirbagheri,

2007).

The negative correlation found between FIM and

kinematic variables after treatment in the IG could

be due to the limitations of the FIM with regards to a

subpopulation of SCI where the motor score is not

capable of adequately discriminating the

neurological level. This could be explained by the

fact that it is not evaluation specific for SCI

(Cacho

et al., 2011).

The correlation between strength and kinematic

parameters, measured with MB, indicate that muscle

NEUROTECHNIX2013-InternationalCongressonNeurotechnology,ElectronicsandInformatics

function in SCI has an important role in

characterizing movements of those patients.

This leads us to believe that both strength and

kinematics performance, are requirements for a

smooth and harmonious movement

(Cacho et al.,

2011).

The relationship between MI and kinematic

variables showed the strongest positives

correlations. This may be due to the fact that as the

motor level is higher, the ROM is bigger.

In most cases, the correlations indexes (CCI) are

higher than 0.70, which is the lower limit to be

considered reliable. Furthermore, there are several

parameters with a CCI higher than 0.80 which

indicates a very reliable correlation

(Baydal-

Bertomeu et al., 2010).

This study allows us to open a new area of

research based on the validation of different motor

capture systems not only as kinematic but also

functional tools, making it possible to measure

activities of daily living in an objective way. These

results can inform the clinicians on the efficacy of

the different rehabilitation methods and their impact

on the patients’ functionality.

Another future field of work is the development

of functional motor models, for use with robotic and

virtual reality rehabilitation programs based on

activities of daily living as well as the opportunity to

adapt each treatment to suit the individual functional

characteristics of the patients.

ACKNOWLEDGEMENTS

We thank the consortium including Foundation

Rafael del Pino, Foundation of the Spanish National

Hospital for Paraplegic Research and Integration

(FUHNPAIIN) and INDRA Systems for funding this

research.

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NEUROTECHNIX2013-InternationalCongressonNeurotechnology,ElectronicsandInformatics