Recognition of EMG signal patterns by neural networks

Y. Matsumura; Yasue Mitsukura; M. Fukumi; N. Akamatsu; Y. Yamamoto; K. Nakaura

doi:10.1109/ICONIP.2002.1198158

Recognition of EMG signal patterns by neural networks

Y. Matsumura, Yasue Mitsukura, M. Fukumi, N. Akamatsu, Y. Yamamoto, K. Nakaura

研究成果: Conference contribution

36 被引用数 (Scopus)

抄録

The paper tries to recognize EMG signals by using neural networks. The electrodes under the dry state are attached to wrists and then EMG is measured. These EMG signals are classified into seven categories, such as neutral, up and down, right and left, wrist to inside, wrist to outside by using a neural network. The neural network learns FFT spectra to classify them. Moreover, we perform the principal component analysis using the simple principal component analysis before we perform recognition experiments. It is shown that our approach is effective to classify the EMG signals by means of computer simulations.

本文言語	English
ホスト出版物のタイトル	ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age
出版社	Institute of Electrical and Electronics Engineers Inc.
ページ	750-754
ページ数	5
巻	2
ISBN（印刷版）	9810475241, 9789810475246
DOI	https://doi.org/10.1109/ICONIP.2002.1198158
出版ステータス	Published - 2002
外部発表	はい
イベント	9th International Conference on Neural Information Processing, ICONIP 2002 - Singapore, Singapore 継続期間: 2002 11月 18 → 2002 11月 22

Other

Other	9th International Conference on Neural Information Processing, ICONIP 2002
国/地域	Singapore
City	Singapore
Period	02/11/18 → 02/11/22

ASJC Scopus subject areas

コンピュータネットワークおよび通信
情報システム
信号処理

文献へのアクセス

10.1109/ICONIP.2002.1198158

他のファイルとリンク

引用スタイル

Matsumura, Y., Mitsukura, Y., Fukumi, M., Akamatsu, N., Yamamoto, Y., & Nakaura, K. (2002). Recognition of EMG signal patterns by neural networks. In ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age (Vol. 2, pp. 750-754). Article 1198158 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICONIP.2002.1198158

Recognition of EMG signal patterns by neural networks. / Matsumura, Y.; Mitsukura, Yasue; Fukumi, M. その他.
ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age. Vol. 2 Institute of Electrical and Electronics Engineers Inc., 2002. p. 750-754 1198158.

研究成果: Conference contribution

Matsumura, Y, Mitsukura, Y, Fukumi, M, Akamatsu, N, Yamamoto, Y & Nakaura, K 2002, Recognition of EMG signal patterns by neural networks. in ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age. vol. 2, 1198158, Institute of Electrical and Electronics Engineers Inc., pp. 750-754, 9th International Conference on Neural Information Processing, ICONIP 2002, Singapore, Singapore, 02/11/18. https://doi.org/10.1109/ICONIP.2002.1198158

Matsumura Y, Mitsukura Y, Fukumi M, Akamatsu N, Yamamoto Y, Nakaura K. Recognition of EMG signal patterns by neural networks. In ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age. Vol. 2. Institute of Electrical and Electronics Engineers Inc. 2002. p. 750-754. 1198158 doi: 10.1109/ICONIP.2002.1198158

@inproceedings{6f9b6659812e4c0ab2096bc744e5f96a,

title = "Recognition of EMG signal patterns by neural networks",

abstract = "The paper tries to recognize EMG signals by using neural networks. The electrodes under the dry state are attached to wrists and then EMG is measured. These EMG signals are classified into seven categories, such as neutral, up and down, right and left, wrist to inside, wrist to outside by using a neural network. The neural network learns FFT spectra to classify them. Moreover, we perform the principal component analysis using the simple principal component analysis before we perform recognition experiments. It is shown that our approach is effective to classify the EMG signals by means of computer simulations.",

author = "Y. Matsumura and Yasue Mitsukura and M. Fukumi and N. Akamatsu and Y. Yamamoto and K. Nakaura",

year = "2002",

doi = "10.1109/ICONIP.2002.1198158",

language = "English",

isbn = "9810475241",

volume = "2",

pages = "750--754",

booktitle = "ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "9th International Conference on Neural Information Processing, ICONIP 2002 ; Conference date: 18-11-2002 Through 22-11-2002",

}

TY - GEN

T1 - Recognition of EMG signal patterns by neural networks

AU - Matsumura, Y.

AU - Mitsukura, Yasue

AU - Fukumi, M.

AU - Akamatsu, N.

AU - Yamamoto, Y.

AU - Nakaura, K.

PY - 2002

Y1 - 2002

N2 - The paper tries to recognize EMG signals by using neural networks. The electrodes under the dry state are attached to wrists and then EMG is measured. These EMG signals are classified into seven categories, such as neutral, up and down, right and left, wrist to inside, wrist to outside by using a neural network. The neural network learns FFT spectra to classify them. Moreover, we perform the principal component analysis using the simple principal component analysis before we perform recognition experiments. It is shown that our approach is effective to classify the EMG signals by means of computer simulations.

AB - The paper tries to recognize EMG signals by using neural networks. The electrodes under the dry state are attached to wrists and then EMG is measured. These EMG signals are classified into seven categories, such as neutral, up and down, right and left, wrist to inside, wrist to outside by using a neural network. The neural network learns FFT spectra to classify them. Moreover, we perform the principal component analysis using the simple principal component analysis before we perform recognition experiments. It is shown that our approach is effective to classify the EMG signals by means of computer simulations.

UR - http://www.scopus.com/inward/record.url?scp=84964533498&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84964533498&partnerID=8YFLogxK

U2 - 10.1109/ICONIP.2002.1198158

DO - 10.1109/ICONIP.2002.1198158

M3 - Conference contribution

AN - SCOPUS:84964533498

SN - 9810475241

SN - 9789810475246

VL - 2

SP - 750

EP - 754

BT - ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 9th International Conference on Neural Information Processing, ICONIP 2002

Y2 - 18 November 2002 through 22 November 2002

ER -

Recognition of EMG signal patterns by neural networks

抄録

Other

ASJC Scopus subject areas

文献へのアクセス

他のファイルとリンク

フィンガープリント

引用スタイル