Electrocardiogram analysis with adaptive feature selection and support vector machines

Wen Chung Kao*, Chun Kuo Yu, Chia Ping Shen, Wei Hsin Chen, Pei Yung Hsiao

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

7 引文 斯高帕斯(Scopus)

摘要

Electrocardiogram (ECG) analysis is one of the most important approaches to cardiac arrhythmia detection. In this paper, we propose an ECG analysis approach with adaptive feature selection and support vector machines (SVMs). Many wavelet transform-based coefficients are used as candidates, but only a few coefficients are selected for classification problem of each class pair. In addition, the several variation classes are partitioned into two or more subclasses to improve the training efficiency of SVMs. The experimental results show that the proposed ECG analysis approach can obtain high recognition rate and reliable results.

原文英語
主出版物標題APCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems
頁面1783-1786
頁數4
DOIs
出版狀態已發佈 - 2006
事件APCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems - , 新加坡
持續時間: 2006 十二月 42006 十二月 6

出版系列

名字IEEE Asia-Pacific Conference on Circuits and Systems, Proceedings, APCCAS

其他

其他APCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems
國家/地區新加坡
期間2006/12/042006/12/06

ASJC Scopus subject areas

  • 電氣與電子工程

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