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Wavelet thresholding technique for sEMG denoising by baseline estimation

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journal contribution
posted on 21.05.2015, 09:06 authored by Luca Bartolomeo, Massimiliano ZeccaMassimiliano Zecca, Salvatore Sessa, Atsuo Takanishi
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 cable motion artefacts, but still there are many limitations in denoising the baseline. In this paper, we introduce a new technique, named baseline adaptive denoising algorithm (BADA), for denoising the sEMG signal by wavelet thresholding procedure. In particular, the thresholds are estimated using the same baseline signal with fixed and adaptive techniques. Eventually, we verify that the proposed adaptive method performs better than the standard Donoho technique and different variations, in term of noise cancellation and distortion of the signal, quantified by a new suggested indicator of the denoising quality. Copyright © 2012 Inderscience Enterprises Ltd.

Funding

This research has been supported by the G-COE Global Robot Academia Program in Waseda University, Japan and partially by a Grant by STMicroelectronics. This research has been conducted at Humanoid Robotics Institute, in collaboration with the G-COE Global Robot Academia. The authors would like to express their gratitude to Okino Industries LTD, Japan ROBOTECH LTD, SolidWorks Corp, Dyden, for their support to the research.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

International Journal of Computer Aided Engineering and Technology

Volume

4

Issue

6

Pages

517 - 534

Citation

BARTOLOMEO, L. ... et al, 2012. Wavelet thresholding technique for sEMG denoising by baseline estimation. International Journal of Computer Aided Engineering and Technology, 4 (6), pp. 517 - 534.

Publisher

© Inderscience

Version

SMUR (Submitted Manuscript Under Review)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2012

Notes

This article was published in the International Journal of Computer Aided Engineering and Technology [© Inderscience]. The definitive version is available at: http://dx.doi.org/10.1504/IJCAET.2012.049573

ISSN

1757-2657

eISSN

1757-2665

Language

en