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

• Main Authors: Ashkenazy, Y, Lewkowicz, M, Levitan, J, Moelgaard, H, Thomsen, P. E. Bloch, Saermark, K
• Format: Journal Article
• Language: English
• Published: 24.04.1998
• Subjects: Physics - Adaptation and Self-Organizing Systems; Physics - Biological Physics; Physics - Chaotic Dynamics; Physics - Data Analysis, Statistics and Probability; Physics - Medical Physics; Quantitative Biology - Biomolecules; Quantitative Biology - Cell Behavior; Quantitative Biology - Genomics; Quantitative Biology - Molecular Networks; Quantitative Biology - Neurons and Cognition; Quantitative Biology - Other; Quantitative Biology - Populations and Evolution; Quantitative Biology - Quantitative Methods; Quantitative Biology - Subcellular Processes; Quantitative Biology - Tissues and Organs
• DOI: 10.48550/arxiv.physics/9804030

Fractals, Vol. 6 No. 3 (1998) 197-203 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.