Title :
Detection of nonlinearity in HRV using cyclostationary analysis
Author :
Seydnejad, S.R. ; Kitney, R.I.
Author_Institution :
Dept. of Biol. & Med. Syst., Imperial Coll. of Sci., Technol. & Med., London, UK
fDate :
10/1/1999 12:00:00 AM
Abstract :
A novel approach for detection of Volterra type nonlinearity in the neurocardiovascular system based on cyclic mean analysis is presented. Metronome breathing is employed to provide a sinusoidal input to the neurocardiovascular system in which Heart Rate Variability (HRV) and Blood Pressure Variation (BPV) are considered as its outputs. The presence of (self) frequency coupling detected by cyclic mean analysis reveals the existence of a polynomial nonlinearity in HRV and BPV
Keywords :
biocontrol; cardiovascular system; electrocardiography; haemodynamics; neurophysiology; physiological models; pneumodynamics; polynomials; BPV; Blood Pressure Variation; HRV; Heart Rate Variability; Volterra type nonlinearity; cyclic mean analysis; cyclostationary analysis; metronome breathing; neurocardiovascular system; nonlinearity detection; polynomial nonlinearity; self frequency coupling; sinusoidal input; Blood pressure; Couplings; Frequency; Harmonic analysis; Heart rate variability; Nonlinear systems; Phase detection; Polynomials; Signal analysis; Signal processing;
Conference_Titel :
[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint
Print_ISBN :
0-7803-5674-8
DOI :
10.1109/IEMBS.1999.804147
