Wavelet thresholding technique for sEMG denoising by baseline estimation

Luca Bartolomeo, Massimiliano Zecca, Salvatore Sessa, Atsuo Takanishi

Research output: Contribution to journalArticle

8 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 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.

Original languageEnglish
Pages (from-to)517-534
Number of pages18
JournalInternational Journal of Computer Aided Engineering and Technology
Volume4
Issue number6
DOIs
Publication statusPublished - 2012

Keywords

  • SEMG
  • Surface Electromyography
  • Wavelet Denoising

ASJC Scopus subject areas

  • Software
  • Engineering(all)
  • Computer Science Applications

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