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

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

Fondazione IRCCS Ca' Granda- Ospedale Maggiore Policlinico

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Unknown Host Publication Title
Editors	Antonio Luque, A.R. Figueiras Vidal, J.M.R. Delgado
Publisher	IEEE
Pages	131-134
Number of pages	4
ISBN (Print)	0444878475
Publication status	Published - 1985

ASJC Scopus subject areas

Engineering(all)

Cite this

AUTOREGRESSIVE MODELLING AND SPECTRAL ESTIMATION FOR THE QUANTIFICATION OF NEURAL CONTROL MECHANISMS ON HEART RATE VARIABILITY SIGNAL. / Baselli, Giuseppe; Cerutti, Sergio; Civardi, Silvia; Lombardi, Federico; Mallani, Alberto; Pagani, Massimo.

Unknown Host Publication Title. ed. / Antonio Luque; A.R. Figueiras Vidal; J.M.R. Delgado. IEEE, 1985. p. 131-134.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Civardi, Silvia

AU - Lombardi, Federico

AU - Mallani, Alberto

AU - Pagani, Massimo

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Y1 - 1985

N2 - 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).

AB - 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).

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

Abstract

ASJC Scopus subject areas

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