Fundamental research on surface electromyography analysis using discrete wavelet transform—an analysis of the central nervous system factors affecting muscle strength

Abstract

[Purpose] We aimed to investigate the central nervous system factors that affect muscle strength based on the differences in load and time using the discrete wavelet transform, which is capable of a time-frequency-potential analysis. [Participants and Methods] Surface electromyography (EMG) of the right upper bicep muscle in 16 healthy adult males were measured at 10% MVC (maximum voluntary isometric contraction), 30%, 50%, 70%, and 80% to 100% MVC. We used a discrete wavelet transform for the electromyographic analysis and calculated the median instantaneous frequency spectrum (MDF) and frequency band component content rate (FCR) at 1-ms intervals as well as their spectrum integrated values (I-EMG). [Results] MDF and FCR tended to be high throughout the measurements. Specifically, the high-frequency band component content rate was high at the time of low muscle strength; fast-twitch muscle fibers may be involved during these muscle contractions. We found significant changes in the I-EMG as the muscle strength increased from 10% MVC to 100% MVC. [Conclusion] Analyzing the surface electromyograph using discrete wavelet transform enabled us to assess the central nervous system factors that increase in the EMG amplitude integrated values and change in the median instantaneous frequency spectrum and in the frequency band component content rate.