Pressure Insole for Gait and Balance Estimation

Stroke leads to impairment in motor ability, gait, and balance, due to brain tissue damage [1]. Clinical therapy following stroke aims at improving mobility and functional capacity. However, there is lack of objective information about subject’s performance once they are transferred home [2].
A wearable, unobtrusive system is needed to describe and compare clinical capacity and performance in a home setting. Systems have been designed to provide holistic information about the subject’s gait and balance [2], [3]. They have shown differences in the capacity and performance of the subject by using a range of measures to estimate gait and balance.
However, these systems are obtrusive and require a long time to set up. This project addresses the need for a wearable and minimal sensing system with an unobtrusive set up. Pressure insoles are inconspicuous, and when coupled with an Inertial Measurement Unit (IMU), several gait and balance measures can be estimated.
In this study, a 1-D pressure insole system (MEDILOGIC®) is coupled with an IMU (Xsens) to obtain qualitative gait and balance measures, including Step length and width, Centre of Pressure, Extended Centre of Mass, and compared against a 3-D system, the Force Shoes™ (Xsens) [4], [5]. The results will be used to validate the use of a 1-D system for gait and balance measures. The results will also be used in designing a wearable in-shoe system that can be used in daily life monitoring for stroke subjects.

The study is a part of project 7 of NeuroCIMT, funded by the Dutch National foundation STW.

REFERENCES
[1] S. F. Tyson, M. Hanley, J. Chillala, A. Selley, and R. C. Tallis, “Balance disability after stroke.,” Phys. Ther., vol. 86, no. 1, pp. 30–38, 2006.
[2] B. Klaassen, B.-J. F. van Beijnum, M. Weusthof, D. Hof, F. B. van Meulen, Ed Droog, H. Luinge, L. Slot, A. Tognetti, F. Lorussi, R. Paradiso, J. Held, A. Luft, J. Reenalda, C. Nikamp, J. H. Buurke, H. J. Hermens, and P. H. Veltink, “A Full Body Sensing System for Monitoring Stroke Patients in a Home Environment,” Commun. Comput. Inf. Sci., vol. 511, pp. 378–393, 2016.
[3] S. J. M. Bamberg, A. Y. Benbasat, D. M. Scarborough, D. E. Krebs, and J. A. Paradiso, “Gait analysis using a shoe-integrated wireless sensor system.,” IEEE Trans. Inf. Technol. Biomed., vol. 12, no. 4, pp. 413–23, 2008.
[4] A. L. Hof, M. G. J. Gazendam, and W. E. Sinke, “The condition for dynamic stability,” J. Biomech., vol. 38, no. 1, pp. 1–8, 2005.
[5] F. B. Van Meulen, D. Weenk, E. H. F. Van Asseldonk, and H. M. Schepers, “Analysis of dynamic balance during functional walking in stroke survivors,” PLoS One, pp. 1–29.