Title :
AR spectral estimation in the analysis of HRV signal in patients with ectopies during dialytic sessions
Author :
Signorini, M.G. ; Cerutti, Sergio
fDate :
31 Oct-3 Nov 1996
Abstract :
An AutoRegressive (AR) model spectral estimation is employed in the study of the Heart Rate Variability (HRV) signal obtained during hemodialytic (HD) treatments characterized by the presence of numerous cardiac arrhythmias. The AR spectral estimation is implemented in a such a way to reduce the impact of ectopic beats on the analysis of HRV signal. The spectral parameters (LF, HF powers, LF/HF ratio), which are able to quantify the sympatho-vagal balance in the setting of heart rate values, are estimated by means of a batch spectral analysis with the aim to extract more information about the mechanisms regulating cardiac frequency during HD sessions
Keywords :
electrocardiography; medical signal processing; patient treatment; physiological models; spectral analysis; ECG analysis; autoregressive model spectral estimation; cardiac arrhythmias; cardiac frequency regulating mechanisms; ectopic beats; heart rate variability signal; hemodialytic treatments; spectral parameters; sympathovagal balance quantification; Biomedical engineering; Control systems; Hafnium; Heart rate variability; High definition video; Hospitals; Medical treatment; Resonant frequency; Signal analysis; Spectral analysis;
Conference_Titel :
Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE
Conference_Location :
Amsterdam
Print_ISBN :
0-7803-3811-1
DOI :
10.1109/IEMBS.1996.647597
