DocumentCode
2467754
Title
Time series modeling of heart rate dynamics
Author
Bennett, F.M. ; Christini, D.J. ; Ahmed, H. ; Lutchen, K. ; Hausdorff, J.M. ; Oriol, N.
Author_Institution
Beth Israel Hospital, Boston, MA, USA
fYear
1993
fDate
5-8 Sep 1993
Firstpage
273
Lastpage
276
Abstract
Autoregressive (AR), autoregressive-moving average (ARMA), bilinear (BL), and polynomial autoregressive (PAR) models were fit to heart rate time series obtained from 9 subjects in the supine position. For each data set and model structure, model order was determined by the Akaike Information Criteria (AIC). For all data sets, the nonlinear BL model had a lower residual variance and AIC compared to AR models. In most cases, BL models provided a better fit to the data than either ARMA or PAR models. For most data sets, the nonlinear BL model provides a more accurate representation of HR dynamics compared to the other model structures tested
Keywords
cardiology; physiological models; time series; Akaike Information Criteria; autoregressive-moving average model; bilinear model; heart rate dynamics; heart rate time series; model order; model structure; polynomial autoregressive model; residual variance; supine position; time series modeling; Heart rate; Hospitals; Least squares approximation; Nonlinear dynamical systems; Parameter estimation; Physiology; Polynomials; Predictive models; Testing; White noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Computers in Cardiology 1993, Proceedings.
Conference_Location
London
Print_ISBN
0-8186-5470-8
Type
conf
DOI
10.1109/CIC.1993.378451
Filename
378451
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