AUTOREGRESSIVE MODELLING AND SPECTRAL ESTIMATION FOR THE QUANTIFICATION OF NEURAL CONTROL MECHANISMS ON HEART RATE VARIABILITY SIGNAL.

Giuseppe Baselli, Sergio Cerutti, Silvia Civardi, Federico Lombardi, Alberto Mallani, Massimo Pagani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Methods of autoregressive parametrization and power spectral estimation are applied to the heart rate variability (HRV) signal in the ECG of normal and pathological subjects. The authors describe some HRV signal processing techniques and evaluate their capabilities for diagnostic classification in various pathologies of the cardiovascular system. The use of online processing of HRV signals is also illustrated for patients undergoing exercise testing (cycloergometer). The proposed methods of signal processing seem to well quantify the variations induced on the ECG tracings by different and selective activation of the neural control systems of heart rate and blood pressure (sympathetic and parasympathetic nervous systems).

Original languageEnglish
Title of host publicationUnknown Host Publication Title
EditorsAntonio Luque, A.R. Figueiras Vidal, J.M.R. Delgado
PublisherIEEE
Pages131-134
Number of pages4
ISBN (Print)0444878475
Publication statusPublished - 1985

ASJC Scopus subject areas

  • Engineering(all)

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