EMG signal decomposition using wavelet transformation with respect to different wavelet and a comparative study

摘要

Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development and modern Human Computer Interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. For properly analyze EMG signal there need good quality of decomposition so that it can reveal the total characteristics of EMG signals. Because EMG signal is Non-Stationary signal so it needs such a method that can decompose non-stationary signal thus wavelet decomposition is a good choice for this type. There are different types of wavelet available. Henceforth, it is necessary that proper attempt should be taken to choice the best one. Here analyses of EMG Signals were made by Various Wavelet Decomposition method with different types of wavelet and it illustrates the comparative study on best possible energy localization in the time-scale plane in order to show the performance. Thus we can choice the right one. The EMG signals used for this analysis - were found both from locally collected as well as from www.emglab.net[5] which provides EMG signal related raw data and other facilities.