COMPENSATORY MOVEMENT DETECTION

THROUGH INERTIAL SENSOR POSITIONING

FOR POST-STROKE REHABILITATION

Carla M. Borges

1,2

, Claudia Silva

, Antonio J. Salazar

1,2

, Ana S. Silva

1,2

, Miguel V. Correia

1,2

Rubim S. Santos

and João P. Vilas-Boas

Instituto de Engenharia de Sistemas e Computadores do Porto (INESC Porto), R. Dr. Roberto Frias 378, Porto, Portugal

Faculdade de Engenharia, Universidade do Porto, R. Dr. Roberto Frias s/n, Porto, Portugal

Centro de Estudos do Movimento e Actividade Humana (ESTSP-IPP), R. Valente Perfeito 322, V. N. Gaia, Portugal

CIFI2D, Faculdade de Desporto da Universidade do Porto, Rua Dr. Plácido Costa 91, Porto, Portugal

Keywords: Rehabilitation, Stroke patients, Compensatory movements, Sensor positioning, Accelerometry.

Abstract: An increasing ageing society and consequently rising number of post-stroke related neurological

dysfunction patients are forcing the rehabilitation field to adapt to ever-growing demands. In parallel, an

unprecedented number of research efforts and technological solutions meant for human monitoring are

continuously influencing traditional methodologies, causing paradigm shifts; extending the therapist patient

dynamics. Compensatory movements can be observed in post-stroke patient when performing functional

tasks. Although some controversy remains regarding the functional benefits of compensatory movement as

a way of accomplish a given task, even in the presence of a motor deficit; studies suggest that such

maladaptive strategies may limit the plasticity of the nervous system to enhance neuro-motor recovery. This

preliminary study intends to aid in the development of a system for compensatory movement detection in

stroke patients through the use of accelerometry data. A post-stroke patients group is presented and

discussed, instructed to perform reach and press movements while sensors were positioned at different

location on the arm, forearm and trunk, in order to assess sensor positioning influence. Results suggest that

P1 is advantageous for compensatory elevation movement detection at the shoulder; P4 seems the most

appropriate for detecting the abduction; and P5 presents a reasonable sensitivity for detection of

anteriorization and rotation of the trunk.

1 INTRODUCTION

According to the World Health Organization

(WHO), 15 million people worldwide suffer a stroke

each year, being the leading cause of disability in

adult population (Thrane, Emaus, Askim, Anke,

2011). Stroke is defined as an acute neurological

dysfunction of vascular origin with rapid onset of

signs and symptoms according to the committed

areas of the brain (WHO, 2011). As epidemiological

studies show, disability following stroke can

evidence in the form of neurological dysfunctions

and reduced ability to actively engage in daily

activities, justifying the need for intervention (Geyh

et al., 2004).

Impairment of upper limb function is one of the

most common deficit following stroke, specifically

at the middle cerebral artery (MCA) territory, and to

date, specific rehabilitation remains challenging to a

significant extent, with little agreement on the

procedures to be followed, despite ongoing

published guidelines containing recommendations

on interventions and assessment strategies targeted

towards the diverse areas of post-stroke disability

(Lucca, 2009; Cirstea, Levin, 2007; Geyh et al., 2004).

The predominantly affected arm may present

muscular weakness; abnormal muscle tone, postural

adjustments, and movement synergies;

biomechanical impairments at joints and/or soft

tissues level; incorrect timing of components within

a movement pattern and loss of interjoint

coordination (Cirstea, Ptito, Levin, 2006). In face of

the before mentioned, it is often identified in post-

stroke patients when attempting to move, as in for

reaching an object, the emergence of compensations

297

Borges C., Silva C., J. Salazar A., Silva A., V. Correia M., S. Santos R. and P. Vilas-Boas J..

COMPENSATORY MOVEMENT DETECTION THROUGH INERTIAL SENSOR POSITIONING FOR POST-STROKE REHABILITATION.

DOI: 10.5220/0003798102970302

In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS-2012), pages 297-302

ISBN: 978-989-8425-89-8

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

related to the available motor strategies and

expressed in form of a pathological synergy

(Michaelsen, Dannenbaum, Levin, 2006).

The neurophysiologic explanation highlights the

post-trauma nervous system’s ability to exploit the

motor system’s redundancy by replacing lost motor

patterns elements with new ones to achieve the

desired task (ib.). In fact, it is well known that after a

lesion, the nervous system can be reorganized

producing an adaptive or maladaptive sensoriomotor

behaviour, highlighting thus the importance of the

reorganization through selective afferent input to

optimize internal representation and influence

movement control (Nudo, 2007; Raine, 2009). In

spite of the mentioned, the use of compensations can

also result in secondary complications such as

muscle weakness or contractures due to joint

misalignment and a lack of recovery of isolated joint

movements, as elbow extension, reinforcing the idea

of the maladaptive nature of such novel movement

patterns post injury (Cirstea and Levin, 2007;

Cirstea, et al., 2006).

Recent advances have promoted the development

of wearable/portable solutions for a number of

human monitoring scenarios. In parallel with such

technological advances, new quantified based

human movement models are commencing to

emerge, applicable to neuromotor assessment.

Kinematic models, based on accelerometry and

angle variation, can estimate 3D arm movement and

events such as falls; however, image based analysis

models seem to dominate, influencing

methodologies and protocols to parallel conventional

medical and rehabilitation observational assessment.

2 METHODOLOGY

2.1 Subjects

The sample was composed by two post-stroke

patients receiving physiotherapy care at a

rehabilitation center, part of an umbrella research

project. Participants had to meet the following

inclusion criteria:

1. Confirmatory neuroimaging results of a single,

unilateral stroke in the MCA territory,

sustained at least 3 months prior.

2. Absence of hemispatial neglect.

3. Absence of major visual, perceptual or

cognitive deficits, confirmed by the mini-

mental state examination (MMSE).

4. Active range of motion in the compromised

arm of at least 15º in the shoulder and elbow.

Explicit exclusion criteria included cerebellar or

brain stem lesions; and pain/sub-luxation in the

upper-limb.

Arm motor impairment was evaluated prior to

measurements, as seen on

Table 1, with the arm

subsection of the Fugl-Meyer scale - FMA (Fugl-

Meyer et al., 1975) and the Reach Performance

Scale - RPS (close target). This clinical evaluation

was performed by a team of three experienced

physiotherapists with more than 10 years of clinical

practice in neurological field.

Table 1: Demographic data and clinical scores of stroke

patients.

Subjects

Patient A Patient B

Age/Gender 49/Male 47/Female

Location of lesion LMCA RMCA

Months post-stroke 66 20

RPS Score (close

target)

5/18 12/18

FMA (shoulder, elbow,

forearm)

4/36 20/36

FMA (wrist) 0/10 2/10

FMA (hand) 2/14 12/14

FMA (coordination) 0/6 3/6

LMCA – Left MCA; RMCA – Right MCA

2.2 Experiment Protocol

The subjects were following, at the time,

conventional rehabilitation procedures associated

with their condition, based on the Bobath Concept

principles. This is a problem-solving approach to the

assessment and treatment of individuals with

disturbances of function, movement and postural

control due to a lesion of the central nervous system

(Raine, 2009). Although sitting balance was not

measured directly, all subjects were ambulatory

without aids and had no difficulty in maintaining a

stable sitting posture during data collection.

As reaching is the most common upper-limb

human gesture, one can understand the great amount

of interest devoted to its analysis, having some

studies reported the expected components of

movement, when target is placed in middle line and

in healthy population: elbow flexion at the beginning

of sequence, followed by combined shoulder

flexion, shoulder horizontal adduction and elbow

extension during the middle and later phases of the

reach (Levin et al., 2004).

Each subject was assessed in sitting position,

with a table placed in front of them, at a height

corresponding to the alignment of the iliac crests.

The table limit was coincident with the distal border

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of the subject’s thigh, so as not to interfere with the

arm trajectory. The subjects were instructed to reach

and press a target placed ipsilaterally to the upper

limb in study, in groups of three repetitions (as to

avoid variations due to fatigue) separated by one

minute rest period.

The target’s placement reference was the

anatomical reaching distance of the hand, using the

measured distance from the acromion to the

metacarpophalangeal joint of the thumb (Reisman

and Scholz, 2006; Vandenberghe, Levin, De

Schutter, Swinnen, Jonkers, 2010). The individual

was instructed, after verbal command, to perform the

functional task. The starting position for the

movement followed: shoulder approximately 0 ° of

flexion / extension and 0 ° of internal rotation, elbow

at approximately 100º of flexion, forearm in

pronation with the palm of the hand resting on thigh

(Wagner, Lang, Sahrmann, Edwards, Dromerick,

2007; Michaelsen, Luta, Roby-Brami, Levin, 2001).

Performance was video recorded for posterior cross-

reference.

2.3 System Description and Setup

A simple wearable monitoring device, named

W2M2 (Wireless Wearable Modular Monitoring),

was designed and implement for inertial data

capturing. The device was based on commercially

available components that could be assembled in a

fast manner, without extensive knowledge of

electronics; seeking to reduce overdependence on

collaborating engineers. The resulting sensor

modules had dimensions of 5.5 x 3 x 2.5 centimeters

The main rehabilitation objectives were focused

on the patient’s affected upper limb. In order to

insure sensor placement repeatability, precise bone

landmarks were required. After a physiological

study of the target area and experimental trial of

sensor positioning for assured subject upper limb

mobility and comfort, the following positions were

considered:

• P1, placed under the acromion, following the

line that connects the lateral epicondyle and the

acromion;

• P2, placed on the middle point between lateral

epicondyle and the acromion;

• P3, immediately above lateral epicondyle, in

alignment with acromion;

• P4, immediately below the lateral epicondyle,

after elbow articulation;

• P5 is in the trunk on the T12.

It should be mentioned that although only these

positions were considered for the present study the

ease with which the patients adapted to the presence

of the sensor permits to imply its use in numerous

other locations.

3 RESULTS

The accelerometers data is captured at a frequency

of approximately 100 Hz, which is then transmitted

wirelessly. A smoothing procedure follows applying

a simple moving average smoothing strategy in

order to reduce the influence of noise and

oscillations. Additional plus/minus pseudo-envelope

functions were generated through a moving window

standard deviation approach, according to

Equation 1, in order to provide visual indicators of

signal stability.

envelope

(t)=S

smooth

(



)





S

raw





(1)

where:

envelope

= envelope function;

WSD

= window mean standard

deviation function.

Data was collected from the two target subjects,

using the W2M2 device, at the established points,

for the reach-press and return functional task. A set

of resulting signals are presented on Figure 1,

accompanied by measurements such as maximum,

minimums, segment amplitude variation and base

calibration references, and corresponding video for

posterior cross-reference. Table 2 shows a

comparative description of movement components,

antero-posterior (A-P), superior-inferior (S-I) and

medial-lateral (M-L), for all sensor locations

analysed. A growing sensitivity scale ranging from 1

to 3 was used for the characterization by a team of

physiotherapists.

Table 2: Sensitivity descriptive analysis of movement

components for sensor locations.

Subject A Subject B

A-P S-I M-L A-P S-I M-L

P1 1 3 1 1 3 2

P2 2 1 1 2 2 2

P3 2 2 2 2 2 2

P4 2 2 3 2 2 3

P5 3 3 3 3 3 3

A-P – Anterior-Posterior; S-I – Superior-Inferior;

M-L – Medial-Lateral

COMPENSATORY MOVEMENT DETECTION THROUGH INERTIAL SENSOR POSITIONING FOR

POST-STROKE REHABILITATION

299

4 DISCUSSION

The sample data is presented in Figure 1 showing

accelerometry data measured at all five sensor

locations (referred to as P1, P2, P3, P4 and P5) for

subjects A and B. The inherent difference in

acceleration amplitudes shown especially in X-axis

between subjects is related to the fact they present

opposite compromise limbs (LMCA vs. RMCA).

The discussion that follows is based on the multiple

data collected from both subjects and their

correspondent video records.

From visual analysis, subject A shows evidence

of reduced segmental selectivity and poor shoulder-

elbow interjoint coordination. Limited motor control

of the upper limb (stability/mobility relation) causes

exaggerated oscillation during movement, which

propagates throughout the body. Compensations on

the movement pattern were visually detected, in

particular excessive elevation and abduction of the

shoulder at the beginning of the movement, as well

as anteriorization and rotation of the right hemi-

trunk at the transport phase. Video analysis

confirmed that the subject did not fully complete the

functional task, i.e., the hand approached but did not

press the target.

Subject B presents increased selectivity in the

movement, observed by the shoulder-elbow

interjoint coordination, and reflected in a reduced

compensatory mechanism through shoulder

abduction. The subject presented a degree of tremor

at the distal segments of the upper limb, evident at

the final phase of the movement, which can be

explained by deficit in the stability/mobility relation.

One also verifies some compensation at the trunk

level, in particular with the anteriorization

component. This individual, comparatively with

subject A, presented increased execution times,

being however important to relate that in contrast

with subject A, has the capacity to fully complete

the task.

In relation with sensor position P1, subject A

presents an average movement in the anterior

direction, i.e. anterior-posterior (X-axis), with

reduced pronunciation (short trajectory), which can

be explained by the incapability of fully reaching the

target. Both patients present on the collected data,

elevation and abduction of the shoulder, at the initial

phase of the movement, corroborating the visual

analysis. Subject B shows that the elevation and

abduction resource is also a strategy used on the

return phase of the movement.

In relation with sensor position P2, there exists

an increased displacement in the anterior direction

(X-axis) when compared with P1; however there is a

lack of marked differences observed on the global

pattern of the movement. Such could suggest that P2

offers more movement detection sensitivity when

compared to P1. In reference to the Y-axis, the

opposite seems to occur, i.e., presents reduced

sensibility for such detection when compared with

P1, for both cases. For Z-axis both individuals do

not present marked differences in the gathered

information from P1 and P2.

Sensor position P3 shows some variability

among the patients. The movement in the anterior

direction (X-axis), performed by subject A is more

pronounced when compared with P1; in turn, for

subject B this movement is better detected when

compared to both P1 and P2. A similar situation

occurs in the remaining movements, i.e. superior

direction (Y-axis) and lateral direction (Z-axis).

Subject B presents no pronounced differences

among the sensor position P1, P2 and P3 for the

lateral direction. This could be explained by lack of

evident movement component recruitment as

compensation during the functional task.

Given the localization of position P4, there exists

a need for redefining the detected movement

components by each of the axis. Thus, the

movement in the antero-posterior direction is now

captured by the Y-axis, and the superior-inferior

direction by the X-axis, remaining the Z-axis

capturing the lateral movements. Subject A, did not

present a significant elevation component (X-axis),

which could be related with the deficit to enlist

selective flexion of the elbow. Subject B presents an

increase elevation component, resulting from an

improved shoulder-elbow interjoint coordination,

being able to perform selective flexion of the elbow

as an integrating part of the movement pattern.

The collected data suggests that sensor position

P1 presents increased commitment between

movement detection in the superior direction

(identification of shoulder elevation as

compensation) and an inter-patient variability;

however a larger number of measurements and

varied sample size is required for such validation.

Finally, as for sensor position P5, one verifies

that such position offers increased reproducibility

among trials, while presenting reduced acceleration

variations (less than 0.1 g in most cases), translating

into a reduced movement of the trunk, especially in

the superior-inferior direction (Y-axis). Some

anteriorization (Z-axis) and rotation (X-axis) is

present, which behave has compensations, given the

reduced capacity of enlisting shoulder flexion with

elbow extension (extensor synergy); implying a

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displacement of the trunk as attempting to reach the

target. Subject B presents increased anteriorization

of the trunk when compared to subject A. The

presence of a larger compensation at this level, in a

clinically less affected individual, could be related to

the difference in functional task completion.

Data analysis seems to suggest that the P1

position is advantageous for compensatory

movement detection at the shoulder level, being

however necessary to complement with information

provided by P5, in order to discriminate between

shoulder or trunk elevation. The information

provided by sensor locations P2 and P3 do not seem

to add relevant knowledge to that provided by sensor

position P1. The P4 position seems the most

appropriate for detecting the abduction component

of the limb; however, in relation with the superior-

inferior movement, this particular sensor position is

insufficient for determination of the corporal

segment where the elevation occurs

(shoulder/elbow/trunk), limiting its reliability for

compensatory movement identification in this

direction. Finally, sensor position P5 presents a good

sensitivity for anteriorization and rotation detection,

though lack of additional comparative data with

other locations at the trunk level.

5 CONCLUSIONS

Methods based on quantitative models can help

therapists and patients to effectively improve the

recovery process, by providing objective assessment

and monitoring, contributing to protocol validation

and information sharing. This preliminary study

focused on the determination of upper limb

associated compensatory movement through

accelerometry data and the influence of sensor

positioning.

ACKNOWLEDGEMENTS

The authors would like to thank the Foundation for

Science and Technology of Portugal for their

support of some of the PhD students involved in this

article (SFRH/BD/61396/2009 and

SFRH/BD/60929/2009). Additionally, the authors

would like to acknowledge the contribution of all

volunteers that took part of the testing procedures.

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APPENDIX

Figure 1: Accelerometry data for Subject A and B for locations P1, P2, P3, P4 and P5.

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