Surface electromyogram (sEMG) may have low signal to noise ratios. An adaptive wavelet thresholding technique was developed in this study to remove noise contamination from sEMG signals. Compared with conventional wavelet thresholding methods, the adaptive approach can adjust thresholds based on different signal to noise ratios of the processed signal, thus effectively removing noise contamination and reducing distortion of the EMG signal. The advantage of the developed adaptive thresholding method was demonstrated using simulated and experimental sEMG recordings.
For the questions of deeply researching abnormal neuromuscular coupling and better evaluating motor function of stroke patients with motor dysfunction, an effective intermuscular coherence analysis method and index are studied to explore the neuromuscular oscillation and the pathomechanism of motor dysfunction, based on which an assessment standard of muscle function is established. Firstly, the contrastive analysis about the intermuscular coherence of antagonistic muscle of affected and intact upper limbs of stroke patients was conducted. Secondly, a significant indicator of Fisher's Z-transformed coherence significant indicator was defined to quantitatively describe the coupling differences in certain functional frequency domain between surface electromyogram (sEMG) of affected and intact sides. Further more, the relationship between intermuscular coherence and motor task was studied. Through the analysis of intermuscular coherence during elbow flexion-extension of affected and intact sides, we found that the intermuscular coherence was associated with motor task and the stroke patients exhibited significantly lower beta-band intermuscular coherence in performing the task with their affected upper limbs. More conclusion can be drawn that beta-band intermuscular coherence has been found concerned with Fugle-Meyer scale, which indicates that beta-band intermuscular coherence could be an index assisting in evaluating motor function of patients.