Baseline adaptive Wavelet thresholding technique for sEMG denoising

L. Bartolomeo, M. Zecca, S. Sessa, Z. Lin, Y. Mukaeda, H. Ishii, Atsuo Takanishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

The surface Electromyography (sEMG) signal is affected by different sources of noises: current technology is considerably robust to the interferences of the power line or the cable motion artifacts, but still there are many limitations with the baseline and the movement artifact noise. In particular, these sources have frequency spectra that include also the lowfrequency components of the sEMG frequency spectrum; therefore, a standard all-bandwidth filtering could alter important information. The Wavelet denoising method has been demonstrated to be a powerful solution in processing white Gaussian noise in biological signals. In this paper we introduce a new technique for the denoising of the sEMG signal: by using the baseline of the signal before the task, we estimate the thresholds to apply to the Wavelet thresholding procedure. The experiments have been performed on ten healthy subjects, by placing the electrodes on the Extensor Carpi Ulnaris and Triceps Brachii on right upper and lower arms, and performing a flexion and extension of the right wrist. An Inertial Measurement Unit, developed in our group, has been used to recognize the movements of the hands to segment the exercise and the pre-task baseline. Finally, we show better performances of the proposed method in term of noise cancellation and distortion of the signal, quantified by a new suggested indicator of denoising quality, compared to the standard Donoho technique.

Original languageEnglish
Title of host publication2011 International Symposium on Computational Models for Life Sciences, CMLS-11
Pages205-214
Number of pages10
DOIs
Publication statusPublished - 2011
Event2011 International Symposium on Computational Models for Life Sciences, CMLS-11 - Toyama City, Japan
Duration: 2011 Oct 112011 Oct 13

Publication series

NameAIP Conference Proceedings
Volume1371
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference2011 International Symposium on Computational Models for Life Sciences, CMLS-11
CountryJapan
CityToyama City
Period11/10/1111/10/13

Keywords

  • Surface electromyography
  • Wavelet denoising

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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