Hybrid EMG recognition system by MDA and PCA

Yuji Matsumura; Minoru Fukumi; Yasue Mitsukura

doi:10.1109/ijcnn.2006.247285

Hybrid EMG recognition system by MDA and PCA

Yuji Matsumura, Minoru Fukumi, Yasue Mitsukura

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 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 language	English
Title of host publication	International Joint Conference on Neural Networks 2006, IJCNN '06
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5294-5300
Number of pages	7
ISBN (Print)	0780394909, 9780780394902
DOIs	https://doi.org/10.1109/ijcnn.2006.247285
Publication status	Published - 2006 Jan 1
Externally published	Yes
Event	International Joint Conference on Neural Networks 2006, IJCNN '06 - Vancouver, BC, Canada Duration: 2006 Jul 16 → 2006 Jul 21

Publication series

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

Other

Other	International Joint Conference on Neural Networks 2006, IJCNN '06
Country/Territory	Canada
City	Vancouver, BC
Period	06/7/16 → 06/7/21

ASJC Scopus subject areas

Software

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10.1109/ijcnn.2006.247285

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). Article 1716836 (IEEE International Conference on Neural Networks - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ijcnn.2006.247285

Hybrid EMG recognition system by MDA and PCA. / Matsumura, Yuji; Fukumi, Minoru; Mitsukura, Yasue.
International Joint Conference on Neural Networks 2006, IJCNN '06. Institute of Electrical and Electronics Engineers Inc., 2006. p. 5294-5300 1716836 (IEEE International Conference on Neural Networks - Conference Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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., 1716836, IEEE International Conference on Neural Networks - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 5294-5300, International Joint Conference on Neural Networks 2006, IJCNN '06, Vancouver, BC, Canada, 06/7/16. https://doi.org/10.1109/ijcnn.2006.247285

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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.",

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AB - 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.

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T3 - IEEE International Conference on Neural Networks - Conference Proceedings

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BT - International Joint Conference on Neural Networks 2006, IJCNN '06

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ER -

Hybrid EMG recognition system by MDA and PCA

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