Baseline adaptive Wavelet thresholding technique for sEMG denoising

L. Bartolomeo, M. Zecca, S. Sessa, Z. Lin, Y. Mukaeda, Hiroyuki 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 publicationAIP Conference Proceedings
    Pages205-214
    Number of pages10
    Volume1371
    DOIs
    Publication statusPublished - 2011
    Event2011 International Symposium on Computational Models for Life Sciences, CMLS-11 - Toyama City
    Duration: 2011 Oct 112011 Oct 13

    Other

    Other2011 International Symposium on Computational Models for Life Sciences, CMLS-11
    CityToyama City
    Period11/10/1111/10/13

    Fingerprint

    electromyography
    artifacts
    wrist
    power lines
    physical exercise
    random noise
    cancellation
    cables
    bandwidth
    interference
    thresholds
    electrodes
    estimates

    Keywords

    • Surface electromyography
    • Wavelet denoising

    ASJC Scopus subject areas

    • Physics and Astronomy(all)

    Cite this

    Bartolomeo, L., Zecca, M., Sessa, S., Lin, Z., Mukaeda, Y., Ishii, H., & Takanishi, A. (2011). Baseline adaptive Wavelet thresholding technique for sEMG denoising. In AIP Conference Proceedings (Vol. 1371, pp. 205-214) https://doi.org/10.1063/1.3596644

    Baseline adaptive Wavelet thresholding technique for sEMG denoising. / Bartolomeo, L.; Zecca, M.; Sessa, S.; Lin, Z.; Mukaeda, Y.; Ishii, Hiroyuki; Takanishi, Atsuo.

    AIP Conference Proceedings. Vol. 1371 2011. p. 205-214.

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

    Bartolomeo, L, Zecca, M, Sessa, S, Lin, Z, Mukaeda, Y, Ishii, H & Takanishi, A 2011, Baseline adaptive Wavelet thresholding technique for sEMG denoising. in AIP Conference Proceedings. vol. 1371, pp. 205-214, 2011 International Symposium on Computational Models for Life Sciences, CMLS-11, Toyama City, 11/10/11. https://doi.org/10.1063/1.3596644
    Bartolomeo L, Zecca M, Sessa S, Lin Z, Mukaeda Y, Ishii H et al. Baseline adaptive Wavelet thresholding technique for sEMG denoising. In AIP Conference Proceedings. Vol. 1371. 2011. p. 205-214 https://doi.org/10.1063/1.3596644
    Bartolomeo, L. ; Zecca, M. ; Sessa, S. ; Lin, Z. ; Mukaeda, Y. ; Ishii, Hiroyuki ; Takanishi, Atsuo. / Baseline adaptive Wavelet thresholding technique for sEMG denoising. AIP Conference Proceedings. Vol. 1371 2011. pp. 205-214
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