A comprehensive sensorimotor control model emulating neural activities for planar human arm reaching movements

Functional Electrical Stimulation (FES) has demonstrated potential in clinical applications, but determining the optimal electrical current to stimulate muscles remains challenging due to the intricate coordination of various muscle groups during human movement. In this study, we introduce a novel approach to model and control human arm planar reaching movements. In terms of the model, a comprehensive human upper limb model is developed, taking into account the double-link structure, six muscles, and the connection points between muscles and the skeletal system. Regarding the control, a comprehensive sensorimotor control model emulating neural activities for human arm planar reaching movements is proposed. The control model effectively incorporates the imprecise nature of human visual sensory feedback for arm endpoint positioning and emulates the neural activities to determine appropriate stimulation levels for each of the six constituent muscles, inducing muscle contractions and guiding the skeletal systems to the target positions. The effectiveness of the proposed controller is demonstrated via numerical simulation experiments. Through comparisons with different controllers, it is shown that the proposed controller exhibits superior performance in tracking predefined motion trajectories and robustness in dealing with various skeletal muscle arm parameters.