Individualized on-line monitoring tool to analyse the complex physiological signal of heart beat fluctuations in pigs
Year: 2013
Type: other
Abstract: Quantifying and understanding the complex fluctuations of physiological signals is the focus of many research.The complexity of physiological signals reflect the ability of organisms to adapt and function within an ever changing environment.The most studied physiological signal to reflect the autonomic imbalance in cases of disease, chronic stress and impaired welfare, in both human and animals is Heart Rate Variability (HRV).Given the limitations of current HRV analyses, like spectral or total entropy analyses, it is suggested to improve our understanding by decomposing the heart rate fluctuations with a dynamic model, based on a Bayesian approach for time series analysis.The model consists of three components describing the interbeat-intervals dynamics: (1) level and trend, (2) autoregressive process of order 2 and (3) observation error (white noise).The analysis also detects abrupt changes and slightly growing deteriorations.A dataset with continuous ECG recordings from 2 pigs was analysed.The model decomposed total Heart Rate dynamics successfully in the time domain.So, it was possible to detect abrupt changes and slightly growing deteriorations in RR-interval in terms of the moments of occurrence, the magnitude, the duration and recovery.
Authors: I.D.E. van Dixhoorn, Ginther Andre, E. Lambooij, Brad Kemp, P.W.G. Groot Koerkamp
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W2561571808