A comparative study of denoising sEMG signals

BAŞPINAR U., Senyurek V. Y., DOĞAN B., Varol H. S.

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, cilt.23, sa.4, ss.931-944, 2015 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 23 Sayı: 4
  • Basım Tarihi: 2015
  • Doi Numarası: 10.3906/elk-1210-4
  • Dergi Adı: TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.931-944
  • Anahtar Kelimeler: Surface electromyography, sEMG, empirical mode decomposition, empirical mode decomposition, denoising, wavelet, median filter, EMPIRICAL MODE DECOMPOSITION, MEDIAN FILTERS, NEURAL-NETWORK, TIME-SERIES, WAVELET, ARTIFACT, NOISE
  • Marmara Üniversitesi Adresli: Evet

Özet

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.