Enhancement of EEG-EMG coupling detection using corticomuscular coherence with spatial-temporal optimization.

Corticomuscular coherence (CMC) is widely used to detect and quantify the coupling between motor cortex and effector muscle. It is promisingly used in human-machine interaction (HMI) supported rehabilitation training to promote the closed-loop motor control for stroke patients. However, suffering from weak coherence features and low accuracy in contingent neurofeedback, its application to HMI rehabilitation robot is currently limited. In this paper, we propose the concept of spatial-temporal CMC (STCMC), which is the coherence by refining CMC with delay compensation and spatial optimization. Then, we tested the reliability and effectiveness of STCMC on neurophysiological data of force tracking tasks. Compared with CMC, STCMC not only enhances the coherence significantly between brain and muscle signals, but also produces higher classification accuracy. Further analysis showed that temporal and spatial parameters estimated by the STCMC reflected more detailed brain topographical patterns, which emphasizes the different roles between the contralateral and ipsilateral hemisphere. This study combined delay compensation and spatial optimization to give a new perspective for corticomuscular coupling analysis. It is also feasible to design robotic neurorehabilitation paradigms by the proposed method. .