A discriminant bispectrum feature for surface electromyogram signal classification

Volume: 32, Issue: 2, Pages: 126 - 135
Published: Mar 1, 2010
Abstract
This paper presents a discriminant bispectrum (DBS) feature extraction approach to surface electromyogram (sEMG) signal classification for prosthetic control. The proposed feature extraction method involves two steps: (1) the bispectrum matrix integration, and (2) the Fisher linear discriminant (FLD) projection. We compare DBS with other conventional features, such as autoregressive coefficients, root mean square, power spectral distribution and...
Paper Details
Title
A discriminant bispectrum feature for surface electromyogram signal classification
Published Date
Mar 1, 2010
Volume
32
Issue
2
Pages
126 - 135
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.