Using Body-Worn Sensors for Preliminary Rehabilitation Assessment in Stroke Victims With Gait Impairment

Improving health is an important driving factor of sensor technology applications. To meet the demands of precision medicine for medical rehabilitation and elderly guardianship, using wearable sensors to get kinematics, kinetics, and biochemical information has become an interdisciplinary research hotspot recently. This paper proposed a low-cost, intelligent, and lightweight wearable platform for rehabilitation assessment in stroke victims with gait impairment. The paper starts from the sensor physical properties and human physiology structure, and aims to solve sensor drift problem by zero velocity update algorithm. A complementary filter based on proportional integral controller was adopted to eliminate computational errors. Preliminary clinical gait experiments results showed that the protocol we have designed according to the proposed guidelines had demonstrated to be operatively simple and efficient compared with existing methods. The expectation of this case study is to develop a dedicated tool for supporting diagnosis and rehabilitation in the hospital.