Research Output
R-wave detection using continuous wavelet modulus maxima.
  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%).

  • Date:

    31 December 2003

  • Publication Status:

    Published

  • DOI:

    10.1109/CIC.2003.1291218

  • Dewey Decimal Classification:

    610.7 Medical education, research & nursing

Citation

Romero Legarreta, I., Addison, P., Grubb, N. R., Clegg, G. R., Robertson, C. E., Fox, K. A. A., & Watson, J. N. (2003). R-wave detection using continuous wavelet modulus maxima. In Computers in Cardiology, 2003, 565-568. https://doi.org/10.1109/CIC.2003.1291218

Authors

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;

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