DocumentCode :
2130046
Title :
A robust T-wave alternans detection algorithm based on the wavelet transform and Bootstrap
Author :
Lihuang She ; Mingquan Wang ; Hongyan Wang ; Shi Zhang
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear :
2012
fDate :
16-18 Oct. 2012
Firstpage :
413
Lastpage :
417
Abstract :
In this article, continuous wavelet and Lipschitz indices are used to divide non-stationary T-wave alternans (TWA) in ECG signal into segments. Then Bootstrap method is applied to test the TWA magnitude. Experiments have extracted ECG signal from the database, and form T-wave alternans signal, Gaussian noise, baseline drift; and took a test to MIT´s TWADB (10 groups) data; and in the last part, we have taken the real ECG to test. The achieved results are satisfactory. It has not only effectively reduced effects on the non-stability of TWA, but also solved the problem that the short-term TWA are difficult to test. The correlation coefficient between measurement and simulation of the magnitude of the true value reached to 0.96.
Keywords :
Gaussian noise; bioelectric potentials; electrocardiography; medical signal detection; medical signal processing; statistical analysis; wavelet transforms; Bootstrap method; ECG signal extraction; ECG signal segmentation; Gaussian noise; Lipschitz index; MIT TWADB data; TWA magnitude measurement; TWA magnitude simulation; baseline drift; continuous wavelet transform; correlation coefficient; electrocardiography; nonstationary T-wave alternan detection algorithm; Bootstrap; Lipschitz; T-wave alternans; Wavelet modulus maxima;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2012 5th International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-1183-0
Type :
conf
DOI :
10.1109/BMEI.2012.6512878
Filename :
6512878
Link To Document :
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