Lower Limb Muscle State Transition Control Based on Complex Network

Muscle activation cannot achieve the activation state experienced during normal activity throughout the rehabilitation process, and effectiveness of rehabilitation will be enhanced if the muscle state can be controlled from the “zero EMG” state to the normal motion state. It is challenging to precisely regulate the muscle state during the model establishment process because the lower limb muscle group is a highly interconnected complicated system. Therefore, this study provides a muscle state transfer control method based on complex network control theory. A linear time-invariant functional myoelectric network model is modeled, and the structural controllability of the network is demonstrated using the PBH rank criterion to determine the optimal set of control nodes. Functional Electrical Stimulation is used as an exogenous input to drive state transfer between muscles. The results suggest that the method we propose is effective in controlling muscle state transitions.