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

doi:10.1142/S0218348X98000249

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

Research output: Contribution to journal › Article › peer-review

33 Scopus citations

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 ∼0.035 (for the above mentioned filter), below which individuals are at risk.

Original language	English
Pages (from-to)	197-203
Number of pages	7
Journal	Fractals
Volume	6
Issue number	3
DOIs	https://doi.org/10.1142/S0218348X98000249
State	Published - 1 Jan 1998
Externally published	Yes

ASJC Scopus subject areas

Modeling and Simulation
Geometry and Topology
Applied Mathematics

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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 ∼0.035 (for the above mentioned filter), below which individuals are at risk.",

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AU - Bloch Thomsen, P. E.

AU - Saermark, K.

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AB - 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 ∼0.035 (for the above mentioned filter), below which individuals are at risk.

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Discrimination of the healthy and sick cardiac autonomic nervous system by a new wavelet analysis of heartbeat intervals

Abstract

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