Wrist EMG signals identification using neural network

Tadahiro Oyama, Yasue Mitsukura, Stephen Githinji Karungaru, Satoru Tsuge, Minoru Fukumi

Research output: Contribution to conferencePaperpeer-review

10 Citations (Scopus)

Abstract

Recently, researches of artificial arms and pointing devices using ElectroMyoGram(EMG) have been actively done. However, EMG is usually measured from a part with comparatively big muscular fibers such as arms and shoulders. Therefore, if we can recognize wrist motions using EMG which was measured from the wrist, the range of application will extend furthermore. Moreover, it is predicted that convenience in putting on and taking off the electrode improves. Therefore, we focus on EMG measured from the wrist. In this paper, we aim the construction of wrist EMG recognition system by using fast statistical method and neural network.

Original languageEnglish
Pages4286-4290
Number of pages5
DOIs
Publication statusPublished - 2009 Dec 1
Externally publishedYes
Event35th Annual Conference of the IEEE Industrial Electronics Society, IECON 2009 - Porto, Portugal
Duration: 2009 Nov 32009 Nov 5

Other

Other35th Annual Conference of the IEEE Industrial Electronics Society, IECON 2009
CountryPortugal
CityPorto
Period09/11/309/11/5

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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