A Low Cost Wearable Wireless Sensing System for Capturing Human Arm Postures in Post-Stroke Rehabilitation

C.K. Lim, I.-M. Chen, Z. Luo, and S.H. Yeo (Singapore)


Low cost wearable system, motion capture, rehabilitation


Being able to track human body kinematics allows clinicians to classify and analyze a stroke patient’s progress which aid in the rehabilitation program. Monitoring and capturing real time body motion further permits corrective measures to be implemented for more effective rehabilitation results. Existing motion capture (mocap) system available in the market is either too costly, or complicated and bulky to be efficiently employed for personal use. In this current work, an innovative and unobtrusive wearable sensing system is being proposed. This compact and cost effective mocap approach effectively captures human joint angles and does that hinder limb motion as commonly encountered in other existing systems. The paper details the design and implementation of the proposed sensor and sensing methodology. The tested wireless sensor is able to detect the posture and movement of the human arm with particular attention to its application in post stroke rehabilitation for the healthcare service. Real time experimental data are collected from a subject using a hand exerciser and compared with a commercial motion capture system. The results demonstrate the feasibility and viability of the proposed sensing system in tracking human arm postures and movement.

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