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 |
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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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TY - GEN
T1 - AUTOREGRESSIVE MODELLING AND SPECTRAL ESTIMATION FOR THE QUANTIFICATION OF NEURAL CONTROL MECHANISMS ON HEART RATE VARIABILITY SIGNAL.
AU - Baselli, Giuseppe
AU - Cerutti, Sergio
AU - Civardi, Silvia
AU - Lombardi, Federico
AU - Mallani, Alberto
AU - Pagani, Massimo
PY - 1985
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).
UR - http://www.scopus.com/inward/record.url?scp=0022217308&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0022217308&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0022217308
SN - 0444878475
SP - 131
EP - 134
BT - Unknown Host Publication Title
A2 - Luque, Antonio
A2 - Figueiras Vidal, A.R.
A2 - Delgado, J.M.R.
PB - IEEE
ER -