A Wearable Sensor Based Hand Movement Rehabilitation and Feedback System

RM 216

This research presents a wearable hand rehabilitation system for stroke patients based on digital glove and keyboard games. This is achieved via hand gesture recognition along with hand model animation. In this work, the digital glove with bending sensors is good for motion data collection during hand rehabilitation. The hand animation model, combined with keyboard games, enables the stroke patient under test to see their finger movements and exercise process. In the feedback stage, the rehabilitation evaluation and recommendation are provided based on the recognition of hand gestures. The experimental results have demonstrated a high accuracy on overt gesture recognition and a reasonable accuracy on complex key press gesture recognition.