Detection of Change--Points in the Spectral Density. With Applications to ECG Data
Pierre R. Bertrand (INRIA Saclay - Ile de France), Gilles Teyssi\`ere,, Gil Boudet, Alain Chamoux
TL;DR
This paper introduces a wavelet-based method for detecting change-points in spectral density, specifically applied to heart rate data in ECG signals, revealing shifts in autonomic nervous system activity.
Contribution
It presents a novel wavelet transform approach to identify change-points in spectral density of ECG data, focusing on the orthosympathetic and parasympathetic bands.
Findings
Detected change-points in heart rate spectral density.
Observed distribution shifts in autonomic nervous system bands.
Validated method on ECG data.
Abstract
We propose a new method for estimating the change-points of heart rate in the orthosympathetic and parasympathetic bands, based on the wavelet transform in the complex domain and the study of the change-points in the moments of the modulus of these wavelet transforms. We observe change-points in the distribution for both bands.
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Heart Rate Variability and Autonomic Control · Statistical and numerical algorithms