Recognition from EMG signals by an evolutional method and non-negative matrix factorization

Yuuki Yazama; Yasue Mitsukura; Minoru Fukumi; Norio Akamatsu

doi:10.1007/978-3-540-45224-9_81

Recognition from EMG signals by an evolutional method and non-negative matrix factorization

Yuuki Yazama, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu

Research output: Contribution to journal › Conference article › peer-review

7 Citations (Scopus)

Abstract

In this paper, we propose a method of the noise rejection from a signal acquired from many channels using the Electromyograph (EMG) signals. The EMG signals is acquired by the 4th electrodes. EMG signals of 4ch(es) is decomposed into two processions using Non-Negative Matrix Factorization(NMF). And noise rejection is performed by applying the filter obtained by GA to the decomposed matrix. After performing noise rejection, EGM signals is reconstructed and the acquired EMG signal is recognized. The EMG signals based on 7 operations at a wrist are measured. We show the effectiveness of this method by means of computer simulations.

Original language	English
Pages (from-to)	594-600
Number of pages	7
Journal	Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume	2773 PART 1
DOIs	https://doi.org/10.1007/978-3-540-45224-9_81
Publication status	Published - 2003
Externally published	Yes
Event	7th International Conference, KES 2003 - Oxford, United Kingdom Duration: 2003 Sept 3 → 2003 Sept 5

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

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10.1007/978-3-540-45224-9_81

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title = "Recognition from EMG signals by an evolutional method and non-negative matrix factorization",

abstract = "In this paper, we propose a method of the noise rejection from a signal acquired from many channels using the Electromyograph (EMG) signals. The EMG signals is acquired by the 4th electrodes. EMG signals of 4ch(es) is decomposed into two processions using Non-Negative Matrix Factorization(NMF). And noise rejection is performed by applying the filter obtained by GA to the decomposed matrix. After performing noise rejection, EGM signals is reconstructed and the acquired EMG signal is recognized. The EMG signals based on 7 operations at a wrist are measured. We show the effectiveness of this method by means of computer simulations.",

author = "Yuuki Yazama and Yasue Mitsukura and Minoru Fukumi and Norio Akamatsu",

year = "2003",

doi = "10.1007/978-3-540-45224-9_81",

language = "English",

volume = "2773 PART 1",

pages = "594--600",

journal = "Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)",

issn = "0302-9743",

publisher = "Springer Verlag",

note = "7th International Conference, KES 2003 ; Conference date: 03-09-2003 Through 05-09-2003",

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TY - JOUR

T1 - Recognition from EMG signals by an evolutional method and non-negative matrix factorization

AU - Yazama, Yuuki

AU - Mitsukura, Yasue

AU - Fukumi, Minoru

AU - Akamatsu, Norio

PY - 2003

Y1 - 2003

N2 - In this paper, we propose a method of the noise rejection from a signal acquired from many channels using the Electromyograph (EMG) signals. The EMG signals is acquired by the 4th electrodes. EMG signals of 4ch(es) is decomposed into two processions using Non-Negative Matrix Factorization(NMF). And noise rejection is performed by applying the filter obtained by GA to the decomposed matrix. After performing noise rejection, EGM signals is reconstructed and the acquired EMG signal is recognized. The EMG signals based on 7 operations at a wrist are measured. We show the effectiveness of this method by means of computer simulations.

AB - In this paper, we propose a method of the noise rejection from a signal acquired from many channels using the Electromyograph (EMG) signals. The EMG signals is acquired by the 4th electrodes. EMG signals of 4ch(es) is decomposed into two processions using Non-Negative Matrix Factorization(NMF). And noise rejection is performed by applying the filter obtained by GA to the decomposed matrix. After performing noise rejection, EGM signals is reconstructed and the acquired EMG signal is recognized. The EMG signals based on 7 operations at a wrist are measured. We show the effectiveness of this method by means of computer simulations.

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DO - 10.1007/978-3-540-45224-9_81

M3 - Conference article

AN - SCOPUS:8344265287

SN - 0302-9743

VL - 2773 PART 1

SP - 594

EP - 600

JO - Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

JF - Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

T2 - 7th International Conference, KES 2003

Y2 - 3 September 2003 through 5 September 2003

ER -

Recognition from EMG signals by an evolutional method and non-negative matrix factorization

Abstract

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