Gaussian Mixture Model of Heart Rate Variability

Tommaso Costa, Giuseppe Boccignone and Mario Ferraro

PLOS ONE, 2012, vol. 7, issue 5, 1-9

Abstract: Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0037731

DOI: 10.1371/journal.pone.0037731

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