Atrial fibrillation analysis based on ICA including statistical and temporal source information

Author

Castells, F. ; Igual, J. ; Rieta, J.J. ; Sanchez, C. ; Millet, J.

Author_Institution

Electron. & Telemedicine Res. Group, Univ. Politecnica de Valencia, Spain

Volume

5

fYear

2003

fDate

6-10 April 2003

Abstract

The analysis and characterization of atrial fibrillation requires the prior extraction of the atrial activity from the electrocardiogram, where the independent atrial and ventricular activities are combined in addition to noise. An independent component analysis method is proposed where additional knowledge about the time and statistical structure of the sources is incorporated. Finally, a combined method based on maximum likelihood and second order blind identification is obtained and validated with results that improve those obtained with traditional ICA algorithms.

Keywords

blind source separation; electrocardiography; independent component analysis; maximum likelihood estimation; medical signal processing; patient diagnosis; ICA; atrial activity; atrial fibrillation analysis; blind source separation; electrocardiogram; independent component analysis; maximum likelihood identification; second order blind identification; source statistical information; source temporal information; ventricular activity; Additive white noise; Atrial fibrillation; Biomedical engineering; Electrocardiography; Gaussian noise; Independent component analysis; Information analysis; Maximum likelihood estimation; Signal processing algorithms; Source separation;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on

ISSN

1520-6149

Print_ISBN

0-7803-7663-3

Type

conf

DOI

10.1109/ICASSP.2003.1199876

Filename

1199876