Incremental learning method in wrist EMG recognition system

Tadahiro Oyama; Yuji Matsumura; Stephen Karungaru; Satoru Tsuge; Yasue Mitsukura; Minoru Fukumi

doi:10.1109/SICE.2007.4421468

Incremental learning method in wrist EMG recognition system

Tadahiro Oyama, Yuji Matsumura, Stephen Karungaru, Satoru Tsuge, Yasue Mitsukura, Minoru Fukumi

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

1 Citation (Scopus)

Abstract

In a field of pattern recognition, researches of feature extraction and dimension reduction using the Simple-PCA that is an approximation algorithm of the principal component analysis (PCA) are actively conducted. In such a statistical method, a lot of algorithms that perform incremental learning by using new incremental data exist. For example, there is an algorithm named Incremental PCA for PCA. However, the algorithm capable of performing incremental learning to the Simple-PCA has not been presented yet. In this paper, we propose Incremental Simple-PCA that introduces an incremental learning function to the Simple-PCA. Moreover, the effectiveness of this algorithm is verified in EMG pattern recognition.

Original language	English
Title of host publication	SICE Annual Conference, SICE 2007
Pages	2819-2822
Number of pages	4
DOIs	https://doi.org/10.1109/SICE.2007.4421468
Publication status	Published - 2007 Dec 1
Externally published	Yes
Event	SICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007 - Takamatsu, Japan Duration: 2007 Sep 17 → 2007 Sep 20

Publication series

Name	Proceedings of the SICE Annual Conference

Other

Other	SICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007
Country/Territory	Japan
City	Takamatsu
Period	07/9/17 → 07/9/20

Keywords

EMG
Incremental learning
Incremental simple-PCA
Pattern recognition
Simple-PCA

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

Access to Document

10.1109/SICE.2007.4421468

Cite this

Oyama, T, Matsumura, Y, Karungaru, S, Tsuge, S, Mitsukura, Y & Fukumi, M 2007, Incremental learning method in wrist EMG recognition system. in SICE Annual Conference, SICE 2007., 4421468, Proceedings of the SICE Annual Conference, pp. 2819-2822, SICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007, Takamatsu, Japan, 07/9/17. https://doi.org/10.1109/SICE.2007.4421468

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title = "Incremental learning method in wrist EMG recognition system",

abstract = "In a field of pattern recognition, researches of feature extraction and dimension reduction using the Simple-PCA that is an approximation algorithm of the principal component analysis (PCA) are actively conducted. In such a statistical method, a lot of algorithms that perform incremental learning by using new incremental data exist. For example, there is an algorithm named Incremental PCA for PCA. However, the algorithm capable of performing incremental learning to the Simple-PCA has not been presented yet. In this paper, we propose Incremental Simple-PCA that introduces an incremental learning function to the Simple-PCA. Moreover, the effectiveness of this algorithm is verified in EMG pattern recognition.",

keywords = "EMG, Incremental learning, Incremental simple-PCA, Pattern recognition, Simple-PCA",

author = "Tadahiro Oyama and Yuji Matsumura and Stephen Karungaru and Satoru Tsuge and Yasue Mitsukura and Minoru Fukumi",

year = "2007",

month = dec,

day = "1",

doi = "10.1109/SICE.2007.4421468",

language = "English",

isbn = "4907764286",

series = "Proceedings of the SICE Annual Conference",

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note = "SICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007 ; Conference date: 17-09-2007 Through 20-09-2007",

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TY - GEN

T1 - Incremental learning method in wrist EMG recognition system

AU - Oyama, Tadahiro

AU - Matsumura, Yuji

AU - Karungaru, Stephen

AU - Tsuge, Satoru

AU - Mitsukura, Yasue

AU - Fukumi, Minoru

PY - 2007/12/1

Y1 - 2007/12/1

N2 - In a field of pattern recognition, researches of feature extraction and dimension reduction using the Simple-PCA that is an approximation algorithm of the principal component analysis (PCA) are actively conducted. In such a statistical method, a lot of algorithms that perform incremental learning by using new incremental data exist. For example, there is an algorithm named Incremental PCA for PCA. However, the algorithm capable of performing incremental learning to the Simple-PCA has not been presented yet. In this paper, we propose Incremental Simple-PCA that introduces an incremental learning function to the Simple-PCA. Moreover, the effectiveness of this algorithm is verified in EMG pattern recognition.

AB - In a field of pattern recognition, researches of feature extraction and dimension reduction using the Simple-PCA that is an approximation algorithm of the principal component analysis (PCA) are actively conducted. In such a statistical method, a lot of algorithms that perform incremental learning by using new incremental data exist. For example, there is an algorithm named Incremental PCA for PCA. However, the algorithm capable of performing incremental learning to the Simple-PCA has not been presented yet. In this paper, we propose Incremental Simple-PCA that introduces an incremental learning function to the Simple-PCA. Moreover, the effectiveness of this algorithm is verified in EMG pattern recognition.

KW - EMG

KW - Incremental learning

KW - Incremental simple-PCA

KW - Pattern recognition

KW - Simple-PCA

UR - http://www.scopus.com/inward/record.url?scp=50249120683&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=50249120683&partnerID=8YFLogxK

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DO - 10.1109/SICE.2007.4421468

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SN - 9784907764289

T3 - Proceedings of the SICE Annual Conference

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EP - 2822

BT - SICE Annual Conference, SICE 2007

T2 - SICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007

Y2 - 17 September 2007 through 20 September 2007

ER -

Incremental learning method in wrist EMG recognition system

Abstract

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Other

Keywords

ASJC Scopus subject areas

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