Paper Info
Title
Wavelet analysis of the Valsalva maneuver: Methodology validation and application to pathological subjects.
Abstract
Abstract The autonomic nervous system (ANS) regulates physiologic processes occurring without conscious control through the sympathetic and the parasympathetic systems. Since the ANS is one of the major determinants of heart rate (HR), evaluation of HR variability is a powerful instrument to quantify sympathetic and parasympathetic activations. Traditional techniques in the frequency domain are not applicable to short non-stationary signals like the RR intervals during the Valsalva maneuver (VM). The aim of this work was to validate the wavelet approach in analyzing the VM: 14 healthy subjects and 9 with autonomic failure underwent two or more VMs for a total of 68 tests. A Daubechies-16 form mother wavelet and the powers associated with the sympathetic (LF band) and parasympathetic (HF) activities were calculated. Each VM performed by the same healthy subject presented similar morphologies for the RR series and LF and HF powers. The inter-subject comparison showed a good agreement in morphology with a greater variability in sympathetic and parasympathetic activations. Pathological subjects presented a good RR series repeatability without any correlation in LF and HF powers. The wavelet approach is a good methodology to discriminate normal from pathological subjects and further longitudinal evaluation are required.
Year
Venue
Field
2017
Biomed. Signal Proc. and Control
Pathological,Artificial intelligence,Autonomic failure,Heart rate,Wavelet,Autonomic nervous system,Pattern recognition,Internal medicine,Simulation,Cardiology,Correlation,Valsalva maneuver,Mathematics,Repeatability
DocType
Volume
Citations 
Journal
35
0
PageRank 
References 
Authors
0.34
2
8
Name
Order
Citations
PageRank
Ivan Corazza154.29
Stefano Giancaterino200.34
Giorgio Barletta300.68
A Cecere431.39
Pietro Guaraldi500.68
Giovanna Calandra-Buonaura600.68
R Zannoli732.41
P Cortelli832.41