A TELEMEDICINE SYSTEM FOR IMPROVED REHABILITATION

OF STROKE PATIENTS

Steffen Ortmann and Peter Langend

orfer

IHP, Im Technologiepark 25, D-15236 Frankfurt, Oder, Germany

Keywords:

Telemedicine, Rehabilitation, Stroke, Body area network, Quality of life.

Abstract:

Analysis showed that costs of long-term care for stroke patients have increased from 13% to 49% of overall

costs in average in recent years. Therefore there is an urgent need for devising an effective long-term care

and rehabilitation strategy for stroke patients, which will involve the patients actively in the process. The

goal of our approach is the development of a telemedicine system which supports ambulant rehabilitation at

home settings for stroke patients with minimal human intervention. This system will combine state-of-the-art

monitoring devices forming a wireless Body Area Network that enable simultaneous measurement of multiple

vital parameters and currently executed movements that are particularly of interest from a Stroke rehabilitation

point of view. It will empower the patient to do more for fast recovery than today and provides clinical experts

with data not available today. By that, it leads also to a better understanding of the stroke recovery process,

higher recovery speed and thus, to reduced healthcare cost while improving patients’ quality of life.

1 MOTIVATION

Stroke is hitting about 2 Million people per year in

Europe (Kirchhof et al., 2009). For these persons the

effect of stroke is that they lose certain physical and

cognitive abilities at least for a certain time period.

More than one third of these patients, i.e., more than

670,000 people, return to their home with some level

of permanent disability leading to a signiﬁcant reduc-

tion of quality of life which affects not only the pa-

tients themselves but also their relatives. Thus, the

manifesto of the Stroke Alliance for Europe (Stroke

Alliance for Europe, 2008) calls on ”all European

Governments to improve the availability of short and

long-term rehabilitation to enable all stroke survivors

to have access to life changing support.” Further,

”telemedicine systems for management of stroke” are

considered to become a key technology to cope with

expected challenges in future stroke care.

There is a strong need to improve the ambulant

care model, in particular, at the home settings, involv-

ing the patients into the care pathway, for achieving

maximal outcome in terms of clinical treatment as

well as quality of life. In addition to the dramatic ef-

fect of stroke for individuals, it has a strong impact

on our society as well. The total cost of stroke in the

EU was calculated to be over 38 billion in 2006. This

ﬁgure included healthcare costs (about 49% of the to-

tal cost), productivity loss due to disability and death

(23% of the total cost) and informal care costs (29%

of the total cost) (Kirchhof et al., 2009).

The prevalence of ageing in the European soci-

eties will lead to an increased number of people suf-

fering from stroke. For example, (Foerch et al., 2008)

predicts that the number of stroke patients in Hessen,

Germany; will increase from 20,846 in 2005 to more

than 35,000 in 2050 which equals to an increase of

nearly 70% within the next four decades. Experts pre-

dicted an increase of even 2.5 times (Go et al., 2001;

Miyasaka et al., 2006) leading to an enormous pres-

sure on the healthcare systems in terms of cost. The

effect on the healthcare cost might be even more sig-

niﬁcant, since the current trend suggests also the ratio

of young and healthy persons to elderly persons to

decrease, so that the informal care cost will be shrink-

ing and thereby directly leading to increased direct

healthcare cost. This will become a real burden for

our economies.

We have just started an EU-funded research

project, called StrokeBack, which addresses both of

the sketched problem areas. The goal of this project is

the development of a telemedicine system which sup-

ports ambulant rehabilitation at home settings for the

stroke patients with minimal human intervention. In

the following, we will introduce objectives and meth-

ods to be investigated by StrokeBack before conclud-

270

Ortmann S. and Langendörfer P..

A TELEMEDICINE SYSTEM FOR IMPROVED REHABILITATION OF STROKE PATIENTS.

DOI: 10.5220/0003871502700274

In Proceedings of the International Conference on Health Informatics (HEALTHINF-2012), pages 270-274

ISBN: 978-989-8425-88-1

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

ing with an outlook on the facts and preliminary re-

sults that we expect to have available soon.

2 OBJECTIVES

The StrokeBack project aims at increasing the reha-

bilitation speed of stroke patients while patients are in

their own home. The beneﬁt we expect from our ap-

proach is twofold. Most patients feel psychologically

better in their own environment than in hospital and

also rehabilitation speed is improved. In addition, we

aim at exploiting the increased motivation of patients

when exercising with a tool similar to a gaming con-

sole. The ability of doing high quality exercises with-

out the need of being directly monitored by a physio-

therapist helps to reduce healthcare cost through min-

imisation of expensive human contact hours. Cur-

rently the quantity of hours performing occupational

(ergotherapeutic) and physiotherapeutic sessions are

restricted to payable effort for patient’s accommoda-

tion, transport or visit of therapists in the patient’s

home. StrokeBack aims at providing new technical

means and service structures to enable patients to en-

hance their healthiness by increasing the number of

training sessions while still being monitored by the

system. By ensuring proper execution of physiother-

apy trainings in an automated guided way, modulated

by appropriate clinical knowledge and in supervised

way only when necessary, StrokeBack empowers the

patients to exercise much more and at better quality

than it is possible today. By that StrokeBack improves

rehabilitation speed, and quality of life of the patient.

The StrokeBack concept will be complemented by

a Patient Health Record (PHR), in which rehabilita-

tion exercises, training measurements and vital data

of the patients will be stored. Thus, the PHR provides

all necessary information medical and rehabilitation

experts need to evaluate rehabilitation success, e.g. to

deduce relations between selected exercises and re-

habilitation speed of different patients, as well as to

assess the overall healthiness of the patient. In addi-

tion, the PHR will be used to provide the patient with

mid-term feedback, e.g., her/his rehabilitation speed

compared to average, as well as improvements over

last day/weeks, in order to keep patients motivation

high.

To summarise, the project goals are achieved by

investigating the following key objectives:

• Telemedicine supervision of rehabilitation exer-

cise.

• Continuous monitoring of impact of the exercises

also in ”normal” life situations.

• Integration of telemedicine rehabilitation and Per-

sonal Health Records for improved long term

evaluation of patient recovery.

• Providing feedback to health care professionals

on the impact of rehabilitation exercises.

Our system will empower the patient to do more

for fast recovery than today, it provides clinical ex-

perts with data not available today and by that it leads

also to a better understanding of the stroke recovery

process, higher recovery speed and thus, to reduced

healthcare cost while improving patients’ quality of

life.

3 APPROACH

Very recently gaming consoles have gained a lot of

attention when being used in the area of rehabilitation

(Anderson et al., 2010; Decker et al., 2009; Deutsch

et al., 2009; Gargin and Pizzi, 2010; John et al., 2009;

Miller, 2007). All publications report on very good

results in terms of speed of the rehabilitation process

and especially patient motivation (Sik-Lanyi et al.,

2005; Sik-Lanyi et al., 2006). A ﬁrst evaluation has

shown that even though the majority of the publica-

tions deal with ”normal” rehabilitation process, e.g.,

after surgery, that similar results hold true for stroke

patients as well (Saposnik et al., 2010).

But most of the published articles about and envi-

sioned applications for computer-aided rehabilitation

of patients have revealed one major drawback. Since

these approaches target to train ﬁne motor skills only,

they require the patients to already possess, or have

recovered up to, a certain level of mobility (Ander-

son et al., 2010). By that, these solutions cannot be

applied to patients having limited mobility such as

spasticity or partial palsy what is the major issue for

patients affected by stroke. These patients cannot be

asked to hold a sensing device by hand or to exercise

by stand. In contrast to that, StrokeBack aims to al-

ready assist in early stage of rehabilitation enabling

highly affected patients to proﬁt from our proposed

monitoring system as well. Our system is designed

for ambulant use and targets to be adjustable to the

abilities of the patient - a patient-centric approach.

For example, it can be used by hemiplegic, paretic

patients as well as wheelchair users, too. By that we

intend to shorten the full time, stationary rehabilita-

tion and treatment program and allow patients to be

reintegrated into normal life as early as possible.

The StrokeBack concept puts the patient into the

centre of the rehabilitation process. It aims at exploit-

ing the fact the patients feel better at home, that it has

A TELEMEDICINE SYSTEM FOR IMPROVED REHABILITATION OF STROKE PATIENTS

271

Figure 1: The StrokeBack rehabilitation cycle follows a patient-centric approach. The patient exercises at home while being

monitored by the StrokeBack system. The exercise schedule and the exercise results are supervised by ambulant physical

therapist care. All data are stored in the PHR to gather long term feedback on the rehabilitation progress.

been shown that patients train more if the training is

combined with attractive training environments. Fig-

ure 1 illustrates how we think the vision of such a

patient centric approach can come true. First the pa-

tients will learn physical rehabilitation exercises from

a therapist at the care centre or in a therapists’ practice

(left part of Figure 1). Then the patients will do the

exercises at home (middle part of Figure 1) and the

StrokeBack system will monitor their execution and

provide real time feedback on whether the execution

was correct or not. In addition, it records the train-

ing results and vital parameters of the patient. These

data will be analysed by medical experts (lower right

part of Figure 1) for assessment of the patient recov-

ery. Also the patient will get midterm feedback on

her/his personal recovery process. In order to ensure

proper guidance of the patient also the therapist will

get information from the PHR to assess the recovery

process and decide whether other training sequences

should be used, which are then introduced to the pa-

tient in the practice again.

In order to provide remote rehabilitation exercises

at gold standard level, i.e., as good as in a face-to-face

training with rehabilitation experts, we plan to exploit

the advanced features of today’s Body Area Networks

(BAN). A BAN attached to the patient enables perma-

nent monitoring of patients activity and vital parame-

ters. We aim to monitor and record the patients’ activ-

ity enabling them to regularly, maybe daily, exercise

independently from the guidance of the physical ther-

apist. With a correct instrumentation we expect to be

able to detect also unwanted additional movements.

In order to achieve a comparable monitoring by cam-

eras at least two of them need to be deployed at the

patient’s home. This is a costly solution which also

bears a privacy risk. Both issues can be solved with

our BAN based solution.

As one possible application, the physical thera-

pist has to look after the patient once a week only to

exploit the level of rehabilitation, to analyse the re-

sults of last exercises based on recorded data and to

take corrective action if necessary. Further, the physi-

cal therapist may show new exercises and conﬁgure a

new exercise schedule. By that, we intend to boost the

rehabilitation process at home. Finally, it allows the

physical therapists and the medical experts to get de-

tailed insights into kind and number of exercises the

patient executes during absence of the care persons.

The envisioned BAN can be worn by the patients

throughout the whole day, which enables comparing

actual movements in their daily life with the correct

movement patterns deﬁned in rehabilitation exercises.

To simplify the conﬁguration process of the system,

we will analyse and evaluate self-learning techniques

for exercise recognition, i.e., the StrokeBack sys-

tem may learn the correct behaviour (patient’s move-

ments) itself when exercises are carried out under in-

struction of the physical therapist.

We will additionally evaluate the feasibility and

requirements of using electronic Personal Health

Records (PHR) to store and document recorded data

and to remotely track the rehabilitation process, e.g.,

HEALTHINF 2012 - International Conference on Health Informatics

272

by the attending doctor. This includes the recordings

done during rehabilitation exercises and during daily

life. The recorded data will be stored and can then be

processed by healthcare professionals. The evaluation

can be used to deduce detailed information of effects

of individual exercises. This feedback can be used to

select exercises for other patients, to assess effective-

ness of exercises for speciﬁc groups of patients etc. In

addition the vital parameters can be used to assess the

healthiness of the patients which might even help to

assess the probability of a further stroke.

4 OUTLOOK

We currently work out the technical and medical ba-

sics for realising the ideas behind the StrokeBack

project. Until the conference, we will be able to

present and discuss insights into the following re-

search areas of the project:

Rehabilitation Exercises. Here, we will focus on

a couple of standard exercises that are to be imple-

mented. As it is common practise for rehabilitation

of stroke patients, these exercises will lean on move-

ments required for daily live, e.g., grasping at differ-

ent objects, lifting a cup, etc. Therefore the scope of

allowed as well as of forbidden movements have to be

determined for each exercise. The most difﬁcult task

to be considered is the fact that every type of exercise

has to be individually adapted to the needs and capa-

bilities of the patient. To enable such patient-centric

individualisation, we intend to experiment with self-

learning techniques that would allow the system to

monitor all movements made when the patient is ex-

ercising under supervision of a physical therapist. By

that, the system can learn the ”ideal” or correct exe-

cution of the exercise and hence, can give adequate

assistance when the patient is exercising alone.

Measurement Methods. Based on the exercises to

be implemented, kind of movements and required key

evaluation data are assessed, upon which the kind

of sensors, e.g., for measuring acceleration and ro-

tation, and their placement on the human body are

determined. Suitable body tracing modelling algo-

rithms will be developed to enable feasible real-time

training. In general, the sensor system should not

only be able to determine correctness of exercises but

must rather be able to autonomously detect wrong or

evasive movements the patient may carry out. Our

idea is to extent the WSN with an Electro-Myo-Gram

(EMG) sensing system for providing static/dynamic

muscle activity monitoring. For example, such sys-

tem would allow detecting hidden evasive movements

in the shoulder or neck when moving the arm, which

are not detectable by acceleration sensors only.

Human Computer Interaction. Human-to-

computer interfaces have to be designed for both

patients and therapists. This means using the system

must be intuitive, clear and self explanatory! On

the one side, the methods for initialisation and

introduction of exercises must be useable not only

by computer specialists but especially by physical

therapists. Here, the self-learning techniques of the

system should properly deal with these issues. On the

other side, our system is to be designed especially for

elderly people, since the majority of patients suffering

from stroke is older than 50 years. Consequently,

the training programs must be kept very simple and

attractive to keep the motivation high. We will follow

a ”what you do is what you see” philosophy, where

each movement of the patient is displayed also on

the monitor in front of the patient. We intend to

use avatar interfaces to which the patient interacts

with like in a computer game, i.e., the patient’s

avatar executes the same movements in real time. In

addition, we would like to exploit known increased

learning effects in rehabilitation, which occur when

providing optical inputs for the patient in addition

to the movements executed. Finally, the system can

replay correct exercise execution at any time, even if

no physical therapist or medical staff is present.

In summary, the StrokeBack main goal is to an-

imate stroke patients to do more for fast recovery

themselves. Our system provides just technical assis-

tance empowering stroke patients to reach their own

rehabilitation goals with adequate means. Last but not

least, the StrokeBack system provides detailed feed-

back about the rehabilitation progress to the patient

and medical care staff as well. From the medical view,

it provides a unique chance to monitor the effects of

various exercises in details. This enables to document

the effectiveness of single exercises when applied to

different patients suffering from various impairments

and hence, it provides stroke experts with high reso-

lution data and knowledge not available today.

ACKNOWLEDGEMENTS

The StrokeBack research project is supported by the

European Commission under the 7th Framework Pro-

gramme through Call (part) identiﬁer FP7-ICT-2011-

7, grant agreement no: 288692.

A TELEMEDICINE SYSTEM FOR IMPROVED REHABILITATION OF STROKE PATIENTS

273

REFERENCES

Anderson, F., Annett, M., and Bischof, W. (2010). Lean

on wii: Physical rehabilitation with virtual reality and

wii peripherals. Annual Review of CyberTherapy and

Telemedicine, 8:181–184.

Decker, J., Li, H., Losowyj, D., and Prakash, V. (2009). Wi-

ihabilitation: rehabilitation of wrist ﬂexion and exten-

sion using a wiimote-based game system. Governor’s

School of Engineering and Technology Research Jour-

nal.

Deutsch, J., Robbins, D., Morrison, J., and Bowlby, P.

(2009). Wii-based compared to standard of care bal-

ance and mobility rehabilitation for two individuals

post-stroke. In Virtual Rehabilitation International

Conference, 2009, pages 117–120. IEEE.

Foerch, C., Misselwitz, B., Sitzer, M., Steinmetz, H.,

and Neumann-Haefelin, T. (2008). Die schlagan-

fallzahlen bis zum jahr 2050. Deutsches

Arzteblatt,

105(26):467–73.

Gargin, K. and Pizzi, L. (2010). Wii-hab: Using the wii

video game system as an occupational therapy inter-

vention with patients in the hospital setting. Health

Policy Newsletter, 23(1):4.

Go, A., Hylek, E., Phillips, K., Chang, Y., Henault, L.,

Selby, J., and Singer, D. (2001). Prevalence of diag-

nosed atrial ﬁbrillation in adults. JAMA: the journal

of the American Medical Association, 285(18):2370.

John, M., H

ausler, B., Frenzel, M., Klose, S., Ernst,

T., B

ucher, J., Seewald, B., Liebach, J., Wolschke,

M., and Klinkm

uller, B. (2009). Rehabilitation im

auslichen umfeld mit der wii ﬁt–eine empirische

studie. Ambient Assisted Living-AAL.

Kirchhof, P., Adamou, A., Knight, E., Lip, G., Norrving, B.,

and de Pouvourville, G. (2009). How Can We Avoid a

Stroke Crisis? Oxford PharmaGenesis. ISBN 978-1-

903539-09-5.

Miller, J. (2007). Wii speeds up the rehab process. USA

Today, 15.

Miyasaka, Y., Barnes, M., Gersh, B., Cha, S., Bailey, K.,

Abhayaratna, W., Seward, J., and Tsang, T. (2006).

Secular trends in incidence of atrial ﬁbrillation in olm-

sted county, minnesota, 1980 to 2000, and implica-

tions on the projections for future prevalence. Circu-

lation, 114(2):119.

Saposnik, G., Teasell, R., Mamdani, M., Hall, J., McIlroy,

W., Cheung, D., Thorpe, K., Cohen, L., and Bayley,

M. (2010). Effectiveness of virtual reality using wii

gaming technology in stroke rehabilitation. Stroke,

41(7):1477–1484.

Sik-Lanyi, C., Geiszt, Z., and Magyar, V. (2006). Using it

to inform and rehabilitate aphasic patients. Informing

Science: International Journal of an Emerging Trans-

discipline, 9:163–179.

Sik-Lanyi, C., Szab

o, J., Pall, A., and Pataky, I. (2005).

Computer-controlled cognitive diagnostics and reha-

bilitation method for stroke patients. ERCIM News,

61:53–54.

Stroke Alliance for Europe (2008). Safe manifesto. In 6th

World Stroke Congress, Vienna, Austria.

HEALTHINF 2012 - International Conference on Health Informatics

274