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Related Experiment Videos

Phonocardiogram signal analysis: a review.

R M Rangayyan1, R J Lehner

  • 1Department of Electrical Engineering, University of Calgary, Alberta, Canada.

Critical Reviews in Biomedical Engineering
|January 1, 1987
PubMed
Summary
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Heart sound analysis, including phonocardiogram (PCG) signals, offers vital diagnostic information but faces challenges. This review explores signal processing techniques to unlock the full potential of heart sound analysis for improved cardiac assessment.

Area of Science:

  • Biomedical Engineering
  • Cardiology
  • Signal Processing

Background:

  • Heart diseases often manifest as changes in heart sounds and murmurs before other clinical signs appear.
  • Physicians primarily use auscultation for initial cardiac assessment, but its effectiveness is limited.
  • Analysis of phonocardiogram (PCG) signals is not widely adopted due to controversies in sound genesis and lack of quantitative methods.

Purpose of the Study:

  • To review the nature of heart sound signals and their diagnostic potential.
  • To explore various signal-processing techniques applied to phonocardiogram (PCG) analysis.
  • To outline new research directions for improved quantitative analysis of cardiac auscultation signals.

Main Methods:

  • Review of existing literature on heart sound signal characteristics.

Related Experiment Videos

  • Analysis of established and emerging signal-processing techniques for PCG data.
  • Identification of current limitations and future research avenues in cardiac sound analysis.

    • Main Results:

    • Heart sound signals contain more information than detectable by human auscultation or visual inspection.
    • Various signal-processing methods can extract quantitative features from PCG signals.
    • Current techniques face challenges related to signal variability and interpretation.

    Conclusions:

    • Quantitative analysis of heart sound signals holds significant promise for early and accurate cardiac diagnosis.
    • Advancements in signal processing are crucial to overcome current limitations in PCG analysis.
    • Further research is needed to establish reliable, quantitative methods for interpreting cardiac auscultation data.