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Estimating qualitative parameters for assessment of body balance and arm function in a simulated ambulatory setting

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ESTIMATING QUALITATIVE PARAMETERS FOR ASSESSMENT OF BODY BALANCE AND ARM FUNCTION IN A SIMULATED AMBULATORY SETTING

Fokke B. van Meulen1*, Jasper Reenalda1,2, Peter H. Veltink1 1

University of Twente

Drienerlolaan 5, 7522 NB, Enschede, the Netherlands 2

Roessingh Research and Development

Roessinghsbleekweg 33b, 75522 AH, Enschede, the Netherlands e-mail: f.b.vanmeulen@utwente.nl

ABSTRACT

Stroke is one of the major causes of disability worldwide. Over 50% of all patients after stroke have impaired balance and/or arm function, which may decrease the performance of many activities of daily living. Patients who suffered a stroke are trained to regain adequate control over their movements with the objective to optimize their daily-life functional performance. However, for optimal guidance of the patient’s training, during as well as after rehabilitation, medical professionals need patient specific capacity and performance information measured while the patient is performing daily life tasks.

The purpose of this study is to demonstrate in stroke patients, the relation between qualitative capacity measures and performance measures while measuring in a simulated ambulatory setting using on-body measurement systems. These measures will be related to results of generally accepted clinical assessments of balance control: Berg balance scale [1] and arm function: upper limb part of the Fugl-Meyer test [2].

Currently, six of a planned total of twenty stroke subjects have been included in a clinical study which has been approved by the local medical ethical committee. Subjects performed activities of daily living in a simulated ambulatory setting: sitting, moving an object over a table, rising up, walking to another room, opening a door and returning an item from another room. The used sensing systems consist of previously developed instrumented shoes with two force sensors and two inertial sensors per shoe (ForceShoes™ - Xsens, Enschede, The Netherlands); an ambulatory 3D human kinematic measurement system (MVN Biomech, Xsens, Enschede, The Netherlands) and an ambulatory EMG recording system (Mobi – TMSi, Oldenzaal, The Netherlands).

Using the on-body sensing system, balance control and upper arm capacity and performance measures are estimated. Qualitative performance measures of balance control are based on Schepers et al. [3] and Hof et al. [4]. Parameters estimated are: step width, step length, stride length, swing/step phase ratio, motion of the centre of mass related to the base of support. Qualitative parameters of arm function are: relative distance between hand, sternum and pelvis; differences in reaching using the affected arm and the non-affected arm and synergies of shoulder abduction/activation and elbow flexion. The use of typical compensatory strategies during daily-life [5], are derived from these parameters.

In a next phase of the INTERACTION project, the qualitative and quantitative parameters developed during the current study, will be evaluated in a textile integrated sensing system which is currently being developed.

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ACKNOWLEDGEMENT

This study is part of the INTERACTION project, which is partially funded by the European Commission under the 7th Framework Programme (FP7-ICT-2011-7-287351)

REFERENCES

[1] K.O. Berg, S. Wood-Danphinee and J.T. Williams, “Measuring balance in the elderly:

preliminary development of an instrument”, Physiotherapy, 41(6), pp. 304-311, 1989.

[2] A.R. Fugl-Meyer, L. Jääskö, I. Leyman, S. Olsson, S. Steglind and others, “The

post-stroke hemiplegic patient. 1. A method for evaluation of physical performance”,

Scandinavian journal of rehabilitation medicine 7(1), pp. 13-31, 1975.

[3] H.M. Schepers, E. van Asseldonk, J.H. Buurke and P.H. Veltink, “Ambulatory estimation

of center of mass displacement during walking”, IEEE Transactions on Biomedical

Engineering, 56(4), pp. 1189-1195, 2009.

[4] A.L. Hof, M.G.J. Gazendam and W.E. Sinke, “The condition for dynamic stability”, Journal of biomechanics, 38(1), pp. 1-8, 2005.

[5] M.C. Cirstea and M.F. Levin, “Compensatory strategies for reaching in stroke”, Brain 123(5), pp. 940-953, 2000.

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