Exploring the differences in surface electromyographic signal between myofascial-pain and normal groups: Feature extraction through wavelet denoising and decomposition

Abstract

Upper-back myofascial pain is an increasingly significant syndrome associated with frequent computer using. However, the changes in neuromuscular functions incurred by myofascial pain are still under-discovered. This study aims to discover the changes in neuromuscular function on the taut band through signal analysis of surface electromyography. We first developed a fully automatic algorithm to detect the duration of an epoch of muscle contraction. Following that, the features of epochs in both time-domain and frequency-domain were extracted from the 13 patients to compare with the measurement from 13 normal subjects. The higher contraction strength with lower median frequency found in the patient group is similar to the reported changes with muscle fatigue. The signal was further analyzed by wavelet energy of 17 levels. The result shows that the energy measured from the patients exceeds that from the normal group at the low frequency band, suggesting that an increasing synchronization level of motor unit recruitment may cause the drop in the median frequency and the increase in contraction strength.