Principal component analysis in ECG signal processing

被引：223
|
作者：
Castells, Francisco [1 ]
Laguna, Pablo
Soernmo, Leif
Bollmann, Andreas
Roig, José Millet
机构：
[1] Univ Politecn Valencia, Dept Elect Engn, E-46071 Valencia, Spain
[2] Univ Zaragoza, Sch Engn, Dept Elect Engn, E-50009 Zaragoza, Spain
[3] Univ Zaragoza, Aragon Inst Engn Res 13A, E-50009 Zaragoza, Spain
[4] Lund Univ, Dept Electrosci, S-22100 Lund, Sweden
[5] Univ Magdeburg, D-39106 Magdeburg, Germany
[6] Univ Hosp, Dept Cardiol, Magdeburg, Germany
来源：
EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING | 2007年 / 2007卷 / 1期
关键词：
D O I：
10.1155/2007/74580
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper reviews the current status of principal component analysis in the area of ECG signal processing. The fundamentals of PCA are briefly described and the relationship between PCA and Karhunen-Loeve transform is explained. Aspects on PCA related to data with temporal and spatial correlations are considered as adaptive estimation of principal components is. Several ECG applications are reviewed where PCA techniques have been successfully employed, including data compression, ST-T segment analysis for the detection of myocardial ischemia and abnormalities in ventricular repolarization, extraction of atrial fibrillatory waves for detailed characterization of atrial fibrillation, and analysis of body surface potential maps.
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收藏
页数：21
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