Combination time-frequency and empirical wavelet transform methods for removal of composite noise in EMG signals

• DOI: 10.12928/telkomnika.v21i6.24939
• Publication Date: 2023-11-03T15:12:25Z
• Authors: Samir Elouaham; Boujemaa Nassiri; Azzedine Dliou; Hicham Zougagh; Najib El Kamoun; Khalid El Khadiri; Sara Said
• Keywords: SIGNAL (programming language); Frequency analysis

Electromyography (EMG) measures the electrical activity in muscles during movement. An electromyography machine records signals from muscle's movements as sound waves. EMG signal measurement is used to help doctors make a quick evaluation identify conditions such muscle problems; dystrophy and neuropathies. The objectives of this study were provide good method that gives proper preprocessing for signals. Often, corrupted by natural noise, which makes analysis difficult; new method, namely empirical wavelet transform, remove noise it clean. non-stationarity more difficult conventional methods time domain frequency domain, do not give much information about time-frequency tool unavoidable, research we periodogram, Choi-Williams, smoothed Pseudo Wigner-Ville. obtained results denoising applications demonstrate high performance Periodogram EWT comparing with other techniques previously published.