The Development of a Motion-Tracking System to Assess the Recovery Level for Stroke Survivors

Abstract

Stroke is a widespread and perilous condition globally, necessitating effective rehabilitation assessment methods. Presently, clinicians rely on manual observation or costly equipment like motion capture systems to evaluate stroke patients’ recovery progress. This study introduces a streamlined measurement system designed for assessing lower limb function recovery in stroke patients. The system employs wearable IMU (Inertial Measurement Unit) sensor modules strategically placed on the lower limbs to capture joint angles. An algorithm processes sensor data to calculate precise joint angles. To counteract environmental interference affecting IMU sensors, a Kalman filter is implemented to minimize errors, providing real-time adjustments for sensor accuracy. Experimental validation, using exercises and criteria from the FUGL-MEYER Assessment, a widely adopted method for evaluating stroke patients’ physical performance, was conducted to compare the proposed system with the VICON motion capture system. Results demonstrated close alignment between the two systems, affirming the proposed system’s reliability, applicability, and practicality for real-life medical evaluations. Importantly, the proposed system offers a cost-effective and portable alternative for measuring joint angles, maintaining effectiveness and precision. In summary, this system offers a straightforward design, easy installation, and affordable hardware, making it a viable and practical solution for evaluating lower limb rehabilitation in stroke patients.