Principal component analysis in ECG signal processing
(2007) In Eurasip Journal on Applied Signal Processing p.74580-74580- Abstract
- 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.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/692660
- author
- Castells, Francisco ; Laguna, Pablo ; Sörnmo, Leif LU ; Bollmann, Andreas and Roig, Jose Millet
- organization
- publishing date
- 2007
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Eurasip Journal on Applied Signal Processing
- pages
- 74580 - 74580
- publisher
- Hindawi Limited
- external identifiers
-
- wos:000248209600001
- scopus:33947228430
- ISSN
- 1110-8657
- DOI
- 10.1155/2007/74580
- language
- English
- LU publication?
- yes
- id
- dff915ae-f506-4bca-bd8c-330a6ce5e179 (old id 692660)
- date added to LUP
- 2016-04-01 16:22:58
- date last changed
- 2022-04-15 04:12:27
@article{dff915ae-f506-4bca-bd8c-330a6ce5e179, abstract = {{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.}}, author = {{Castells, Francisco and Laguna, Pablo and Sörnmo, Leif and Bollmann, Andreas and Roig, Jose Millet}}, issn = {{1110-8657}}, language = {{eng}}, pages = {{74580--74580}}, publisher = {{Hindawi Limited}}, series = {{Eurasip Journal on Applied Signal Processing}}, title = {{Principal component analysis in ECG signal processing}}, url = {{http://dx.doi.org/10.1155/2007/74580}}, doi = {{10.1155/2007/74580}}, year = {{2007}}, }