A comparative study of denoising sEMG signals

Authors

ULVİ BAŞPINAR
VOLKAN YUSUF ŞENYÜREK
BARIŞ DOĞAN
HÜSEYİN SELÇUK VAROL

Abstract

Denoising of surface electromyography (sEMG) signals plays a vital role in sEMG-based mechatronics applications and diagnosis of muscular diseases. In this study, 3 different denoising methods of sEMG signals, empirical mode decomposition, discrete wavelet transform (DWT), and median filter, are examined. These methods are applied to 5 different levels of noise-added synthetic sEMG signals. For the DWT-based denoising technique, 40 different wavelet functions, 4 different threshold-selection-rules, and 2 threshold-methods are tested iteratively. Three different window-sized median filters are applied as well. The SNR values of denoised synthetic signals are calculated, and the results are used to select DWT and median filter method parameters. Finally, 3 methods with the optimum parameters are applied to the real sEMG signal acquired from the flexor carpi radialis muscle and the visual results are presented.

DOI

10.3906/elk-1210-4

Keywords

Surface electromyography, sEMG, empirical mode decomposition, empirical mode decomposition, denoising, wavelet, median filter

First Page

931

Last Page

944

Recommended Citation

BAŞPINAR, U, ŞENYÜREK, V. Y, DOĞAN, B, & VAROL, H. S (2015). A comparative study of denoising sEMG signals. Turkish Journal of Electrical Engineering and Computer Sciences 23 (4): 931-944. https://doi.org/10.3906/elk-1210-4