Volume 6 Number 5 (May 2011)
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JSW 2011 Vol.6(5): 880-886 ISSN: 1796-217X
doi: 10.4304/jsw.6.5.880-886

Classification of Bio-potential Surface Electrode based on FKCM and SVM

Hao Liu1, 2, Xiaoming Tao3, Pengjun Xu1, Guanxiong Qiu2
1School of Textile, Tianjin Polytechnic University, Tianjin, China
2Key Laboratory for Advanced Textile Composite of Ministry of Education, Tianjin Polytechnic University, Tianjin, China
3Institute of Textiles and Clothing, Hong Kong Polytechnic University, Hong Kong, China

Abstract—In this paper, a method which is used for evaluating the performance of bio-potential surface electrode (BSE) with multi-index is presented. The Fuzzy kernel C-means (FKCM) algorithm and KF statistic are employed for classifying the BSE samples and searching an optimal classification amount respectively. Subsequently, a discriminant function is constructed by support vector machines (SVM) for recognizing the new measured samples. Experimental result shows classification correction ratios of improved FKCM algorithm are 96.3% and 85% on the IRIS and BSE dataset according a priori knowledge, furthermore, the recognition correction ratios of SVM algorithm are 96.3% and 90% on the IRIS and BSE dataset.

Index Terms—FKCM, SVM, classification, recognition, biopotential surface electrode


Cite: Hao Liu, Xiaoming Tao, Pengjun Xu, Guanxiong Qiu, "Classification of Bio-potential Surface Electrode based on FKCM and SVM," Journal of Software vol. 6, no. 5, pp. 880-886, 2011.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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