Sensor-Driven Control Algorithms for Active and Passive Hand Rehabilitation in Mirror Therapy

Home-based rehabilitation systems provide effective support for stroke recovery, allowing continuous and accessible therapy. Using hand tracking sensors (HTSs) to create a mirror therapy procedure can enhance precision and adaptability in rehabilitation procedures. However, there is a need to develop effective control algorithms, including specific approaches for both active and passive modes of rehabilitation. This work describes the development of control algorithms for both active and passive hand rehabilitation, aiming to provide precise trajectory tracking and synchronization between the healthy and affected hands during mirror therapy. The HTS captures joint angles of the healthy hand, which provide reference inputs for the control algorithms. These algorithms will drive the movement of the affected hand, enabling a passive range of motion and synchronize active rehabilitation. External force adaptation is integrated into the system for safety and comfort. Results presented in this work demonstrate the possibility of using sensor-driven data for real-time control enhancement in rehabilitation systems. These results suggest the great potential of fusing HTS data with control algorithms to develop accessible, personalized, and effective stroke rehabilitation solutions.