Key result
Computer-based analysis of heart rate signals using approximate entropy, sample entropy, recurrence plots, and Poincare geometry identified various cardiac abnormalities with an accuracy of >95%.
Why the study?
Can computer-based analysis using entropies, recurrence plots, and Poincare geometry accurately diagnose cardiac abnormalities from heart rate signals?
Observational
Can computer-based analysis using entropies, recurrence plots, and Poincare geometry accurately diagnose cardiac abnormalities from heart rate signals?
Computer-based analysis of heart rate variability using non-linear dynamics like approximate entropy and Poincare plots can accurately classify normal and abnormal cardiac states with over 95% accuracy.
May aid automated cardiac diagnosis; leaves open routine use pending prospective validation.
Heart rate variability refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability is important because it provides a window to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computer-based intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Parameters are extracted from the heart rate signals and analysed using computers for diagnostics. This paper describes the analysis of normal and seven types of cardiac abnormal signals using approximate entropy (ApEn), sample entropy (SampEn), recurrence plots and Poincare plot patterns. Ranges of these parameters for various cardiac abnormalities are presented with an accuracy of more than 95%. Among the two entropies, ApEn showed better performance for all the cardiac abnormalities. Typical Poincare and recurrence plots are shown for various cardiac abnormalities.
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Chua et al. (2008) conducted an observational in Cardiac abnormalities. Computer-based analysis using entropies, recurrence plots, and Poincare geometry was evaluated on Diagnostic accuracy for various cardiac abnormalities. Computer-based analysis of heart rate signals using approximate entropy, sample entropy, recurrence plots, and Poincare geometry identified various cardiac abnormalities with an accuracy of >95%.
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