Hybrid EMG recognition system by MDA and PCA

Yuji Matsumura, Minoru Fukumi, Yasue Mitsukura

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

4 Citations (Scopus)

Abstract

In this paper, we propose a recognition system of wrist operation by focusing on ElectroMyoGram (EMG), that is, the living body signal generated with movement of a subject. In previous research, we only performed pattern recognition by Neural Network (NN) and Fast Fourier Transform (FFT). In contrast, in proposal research, we try to improve recognition accuracy and reduce learning-time of system by combining Multi Discriminant Analysis (MDA) and gradual Principal Component Analysis (PCA) based on the PCA result of EMG data. From results of computer simulation, it is shown that our approach is effective for improvement in recognition accuracy and speed.

Original languageEnglish
Title of host publicationInternational Joint Conference on Neural Networks 2006, IJCNN '06
Pages5294-5300
Number of pages7
Publication statusPublished - 2006 Dec 1
EventInternational Joint Conference on Neural Networks 2006, IJCNN '06 - Vancouver, BC, Canada
Duration: 2006 Jul 162006 Jul 21

Publication series

NameIEEE International Conference on Neural Networks - Conference Proceedings
ISSN (Print)1098-7576

Other

OtherInternational Joint Conference on Neural Networks 2006, IJCNN '06
CountryCanada
CityVancouver, BC
Period06/7/1606/7/21

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ASJC Scopus subject areas

  • Software

Cite this

Matsumura, Y., Fukumi, M., & Mitsukura, Y. (2006). Hybrid EMG recognition system by MDA and PCA. In International Joint Conference on Neural Networks 2006, IJCNN '06 (pp. 5294-5300). [1716836] (IEEE International Conference on Neural Networks - Conference Proceedings).