Discrimination of the Healthy and Sick Cardiac Autonomic Nervous System by a New Wavelet Analysis of Heartbeat Intervals

Y. Ashkenazy; M. Lewkowicz; J. Levitan; H. Moelgaard; P. E. Bloch Thomsen; K. Saermark

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Discrimination of the Healthy and Sick Cardiac Autonomic Nervous System by a New Wavelet Analysis of Heartbeat Intervals

Y. Ashkenazy·M. Lewkowicz·J. Levitan·H. Moelgaard·P. E. Bloch Thomsen·K. Saermark

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Abstract

We demonstrate that it is possible to distinguish with a complete certainty between healthy subjects and patients with various dysfunctions of the cardiac nervous system by way of multiresolutional wavelet transform of RR intervals. We repeated the study of Thurner et al on different ensemble of subjects. We show that reconstructed series using a filter which discards wavelet coefficients related with higher scales enables one to classify individuals for which the method otherwise is inconclusive. We suggest a delimiting diagnostic value of the standard deviation of the filtered, reconstructed RR interval time series in the range of $\sim 0.035$ (for the above mentioned filter), below which individuals are at risk.

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Y. Ashkenazy, M. Lewkowicz, J. Levitan, H. Moelgaard, P. E. Bloch Thomsen, K. Saermark. 1998-04-24. Discrimination of the Healthy and Sick Cardiac Autonomic Nervous System by a New Wavelet Analysis of Heartbeat Intervals. https://arxiv.org/abs/physics/9804030

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