IEEE J Biomed Health Inform - Compressed sensing technology-based spectral estimation of heart rate variability using the integral pulse frequency modulation model.

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Resumo

In this paper, a compressed sensing (CS)-based spectral estimation of heart rate variability (HRV) using the integral pulse frequency modulation (IPFM) model is introduced. Previous research in the literature indicated that the IPFM model is widely accepted as a functional description of the cardiac pacemaker, and thus, very useful in modeling the mechanism by which the autonomic nervous system modulates the heart rate (HR). On the other hand, recently CS becomes an emerging technology that has attracted great attention since it is capable of acquiring and reconstructing signals that are considered sparse or compressible, even when the number of measurements is small. Using the IPFM model, we here present a CS-based algorithm for deriving the amplitude spectrum of the modulating signal for HRV assessments. In fact, the application of the CS method into HRV spectral estimation is unprecedented. Numerical results produced by a real RR database of PhysioNet demonstrated that the proposed approach can robustly provide high-fidelity HRV spectral estimates, even under the situation of a degree of incompleteness in the RR data caused by ectopic or missing beats.

Resumo Limpo

paper compress sens csbase spectral estim heart rate variabl hrv use integr puls frequenc modul ipfm model introduc previous research literatur indic ipfm model wide accept function descript cardiac pacemak thus use model mechan autonom nervous system modul heart rate hr hand recent cs becom emerg technolog attract great attent sinc capabl acquir reconstruct signal consid spars compress even number measur small use ipfm model present csbase algorithm deriv amplitud spectrum modul signal hrv assess fact applic cs method hrv spectral estim unpreced numer result produc real rr databas physionet demonstr propos approach can robust provid highfidel hrv spectral estim even situat degre incomplet rr data caus ectop miss beat

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