Symmetric Multifractal Detrended Cross-Correlation Analysis of EEG and sEMG in The Processes of Myodynamia Changes

Abstract

The cross-correlation between the electroencephalogram (EEG) and surface electromyography (sEMG) has important research value both in human-robot integration and intelligent rehabilitation robots. The purpose of this study is to explore the relationship between EEG and sEMG when EEG has different trends. The asymmetric cross-correlation of EEG and sEMG in different states were analyzed by using the multifractal asymmetric detrended cross correlation analysis (MF-ADDCA) method. The synchronous EEG and sEMG in the process of tracking feedback force were analyzed. In order to investigate the dynamic process of asymmetric degree, the rolling window MF-ADDCA method was adopted. The analysis results showed that the asymmetries existed in the cross-correlation between EEG and sEMG and the asymmetric cross-correlation were multifractal. In a resting state, the cross-correlation between EEG and sEMG was symmetric. The asymmetries cross-correlation between EEG and sEMG were stronger in large fluctuations under myodynamia enhancement state, and were stronger in small fluctuations under myodynamia stability state.