부산대학교 도서관

Hybrid systems, which combine Functional Electrical Stimulation (FES) and rehabilitation robots, are highly valuable technologies for people with neurological impairments. These systems provide coordinated assistance to the individual's muscles during functional movements, resulting in therapeutic benefits that arise from the combined advantages of both approaches. However, most of the available hybrid systems lack a cooperative control approach that can effectively synchronize FES and motor assistance with the patient's residual voluntary effort, to maximize the effects on the central nervous system. To address these challenges, we developed an electromyography(EMG)-triggered control framework for hybrid rehabilitation systems: FES is updated repetition by repetition through an iterative learning control, while the motor torque is modulated based on an impedance-based control for small movement corrections. To promote user's involvement both FES and motor assistance are triggered based on the volitional EMG of the subject. This control scheme was tested on 10 healthy subjects using an actuated test bench during knee extension movements. Results showed that, when comparing the fully hybrid solution (FES+motor+volitional) with the execution of passive motor-driven exercises, a decrease of 94% in torque demand is found, without any significant decline in tracking performance. In the future, we will monitor EMG activity also during the exercise to provide real-time feedback on users' active participation and to improve their engagement.