Detection of intermuscular coordination based on the causality of empirical mode decomposition

Considering the stochastic nature of electromyographic (EMG) signals, nonlinear methods may be a more accurate approach to study intermuscular coordination than the linear approach. The aims of this study were to assess the coordination between two ankle plantar flexors using EMG by applying the causal decomposition approach and assessing whether the intermuscular coordination is affected by the slope of the treadmill. The medial gastrocnemius (MG) and soleus muscles (SOL) were analyzed during the treadmill walking at inclinations of 0°, 5°, and 10°. The coordination was evaluated using ensemble empirical mode decomposition, and the causal interaction was encoded by the instantaneous phase dependence of time series bi-directional causality. To estimate the mutual predictability between MG and SOL, the cross-approximate entropy (XApEn) was assessed. The maximal causal interaction was observed between 40 and 75 Hz independent of inclination. XApEn showed a significant decrease between 0° and 5° (p = 0.028), between 5° and 10° (p = 0.038), and between 0° and 10° (p = 0.014), indicating an increase in coordination. Thus, causal decomposition is an appropriate methodology to study intermuscular coordination. These results indicate that the variation of loading through the change in treadmill inclination increases the interaction of the shared input between MG and SOL, suggesting increased intermuscular coordination.