Wavelet Coherence Analysis of Muscle Coupling during Reaching Movement in Stroke

Abstract Agonist-antagonist coordination is essential to ensure the accuracy and stability of voluntary movement, which can be presented by time-varying coupling between agonist-antagonist electromyographic (EMG) signals. To discover the stroke-induced neurological change in paretic muscles, the wavelet coherence is firstly compared with coherence by simulated data and is utilized to represent the time-varying coupling of experimental data during elbow-tracking tasks. The simulation in this study demonstrates that the wavelet coherence is superior to coherence in the detection of short-time coupling between simulated signals. In addition, the experiment in this study is designed to explore the coupling between agonist-antagonist activations during the dynamic process. In the experiment, 10 post-stroke patients and 10 age-matched adults serving as controls were recruited and asked to perform elbow sinusoidal trajectory tracking tasks. Both the elbow angle and EMG signals of biceps and triceps were recorded simultaneously. Experimental results showed that wavelet coherence could represent the time-varying coupling between two EMG signals in the time-frequency domain, and its dynamic character was appropriate in the dynamic process to discover the functional coupling. According to the time and frequency analysis, the lower functional coupling in the post-stroke group and the obvious wavelet coherence difference between the two groups in the lower frequency range suggested a possible hypothesis mechanism that the weakening of coupling between agonist-antagonist muscles in the affected sides might in fact be stroke-induced damage in the direct corticospinal pathways.