DocumentCode :
2569586
Title :
A novel blind source extration method for biomedical signals
Author :
Zhao, Yongjian ; Liu, Boqiang
Author_Institution :
Inf. Eng. Inst., Shandong Univ. at Weihai, Weihai, China
fYear :
2010
fDate :
16-18 April 2010
Firstpage :
348
Lastpage :
352
Abstract :
Biomedical signals are a rich source of information about physiological processes, but they are often contaminated by noise. In order to separate biomedical signals from mixtures effectually, we propose a novel blind source extration method that is robust with respect to the noise. The robustness lies in two-fold: on the one hand,the method does not lead to biassed estimates and, on the other, it minimizes the amount of signal and noise interference on the estimated sources. Based on independent component analysis techniques, the proposed method can give a consistent estimator of the mixing matrix and the noise variance. Preliminary results tested with ECG signals have demonstrated that the proposed method may be promising for blindly separating biomedical signals in the presence of noise and further decompose the mixed signals into subcomponents.
Keywords :
blind source separation; electrocardiography; independent component analysis; medical signal processing; signal denoising; ECG signals; biomedical signals; blind source extraction method; independent component analysis; noise; physiological processes; Additive noise; Biomedical engineering; Covariance matrix; Independent component analysis; Information resources; Noise robustness; Signal analysis; Signal processing; Signal processing algorithms; Working environment noise; Gaussian; biomedical signals; covariance matrix; electrocardiogram data; independent component analysis; regression analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedical Technology (ICBBT), 2010 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6775-4
Type :
conf
DOI :
10.1109/ICBBT.2010.5478942
Filename :
5478942
Link To Document :
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