Simultaneous and Proportional Real-Time Control of Three-DoF Movements Based on Motor Unit Discharges

High-density electromyography (EMG) decomposition technology enables the myoelectric control on the level of individual motor units (MUs). Compared to traditional EMG-based control schemes, the MU-based control strategy exhibits enhanced reliability and superiority in the decoding of continuous motion and real-time control. Current MU-based control schemes are usually limited to one or two degrees of freedom (DoFs), reducing intuitiveness. In this work, we use a graph-based clustering method to associate MUs with multiple wrist/hand movements, realizing three-DoF simultaneous and proportional control (SPC) based on motor unit action potential train (MUAPT) decomposed from high-density EMG signals. The cumulative discharges of MUs within each group were extracted and mapped into multi-DoF motion activations with a multiple linear regression model. The performance of the proposed control scheme was tested on twelve subjects. Each subject controlled a virtual arrow to finish real-time control tasks with both position and velocity-based approaches. The results were promising: the task completion rate reached 89.2% in velocity control mode, and 70% in position control mode, which requires simultaneous activation of multiple DoFs. This study demonstrates the feasibility of three-DoF real-time myoelectric control based on MUAPTs, demonstrating the potential of MUs in creating more intuitive human-machine interfaces.