R-wave detection using continuous wavelet modulus maxima.

Romero Legarreta, I; Addison, Paul; Grubb, N R; Clegg, Gareth R; Robertson, C E; Fox, K A A; Watson, J N

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%).

Citation

Romero Legarreta, I., Addison, P., Grubb, N. R., Clegg, G. R., Robertson, C. E., Fox, K. A. A., & Watson, J. N. (2003, September). R-wave detection using continuous wavelet modulus maxima. Presented at Computers in Cardiology

• Conference Name: Computers in Cardiology
• Start Date: Sep 21, 2003
• End Date: Sep 24, 2003
• Publication Date: 2003
• Deposit Date: Mar 30, 2015
• Peer Reviewed: Peer Reviewed
• Pages: 565-568
• Book Title: Computers in Cardiology, 2003
• ISBN: 0-7803-8170-X
• DOI: https://doi.org/10.1109/CIC.2003.1291218
• Keywords: 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
• Public URL: http://researchrepository.napier.ac.uk/id/eprint/7711
• Publisher URL: http://dx.doi.org/10.1109/CIC.2003.1291218