DocumentCode :
2882818
Title :
R-wave detection using continuous wavelet modulus maxima
Author :
Legarreta, I. Romero ; Addison, Ps ; Grubb, N. ; Clegg, Gr ; Robertson, Ce ; Fox, Kaa ; Watson, Jn
Author_Institution :
Fac. of Eng. & Comput., Napier Univ., Edinburgh, UK
fYear :
2003
fDate :
21-24 Sept. 2003
Firstpage :
565
Lastpage :
568
Abstract :
Modulus maxima derived from the continuous wavelet transform offers an enhanced time-frequency analysis technique for ECG signal analysis. Features within the ECG can be shown to correspond to various morphologies in the continuous modulus maxima domain. This domain has an easy interpretation and offers a good tool for the automatic characterization of the different components observed in the ECG in health and disease. As an application of these properties we have developed an R-wave detector and tested it using patient signals recorded in the Coronary Care Unit of the Royal Infirmary of Edinburgh (attaining a sensitivity of 99.53% and a positive predictive value of 99.73%) and with the MIT/BIH database (attaining a sensitivity of 99.7% and a positive predictive value of 99.68%).
Keywords :
electrocardiography; medical signal detection; medical signal processing; time-frequency analysis; wavelet transforms; Coronary Care Unit; ECG signal analysis; MIT/BIH database; R-wave detection; Royal Infirmary of Edinburgh; continuous wavelet transform; disease; enhanced time-frequency analysis; health; modulus maxima; Continuous wavelet transforms; Detectors; Diseases; Electrocardiography; Morphology; Signal analysis; Testing; Time frequency analysis; Wavelet analysis; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computers in Cardiology, 2003
ISSN :
0276-6547
Print_ISBN :
0-7803-8170-X
Type :
conf
DOI :
10.1109/CIC.2003.1291218
Filename :
1291218
Link To Document :
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