Do nonlinearities play a significant role in short term,beat-to-beat
variability?

Choi, H.G.   Mukkamala, R.   Moody, G.B.   Mark, R.G.  

This paper appears in: Computers in Cardiology 2001
Publication Date: 2001
On page(s): 53-56
Meeting Date: 09/23/2001 - 09/26/2001
Location: Rotterdam, Netherlands
ISBN: 0-7803-7266-2
References Cited: 8
INSPEC Accession Number: 7176635
DOI: 10.1109/CIC.2001.977589
Posted online: 2002-08-06 23:57:50.0

Abstract
Numerous studies of short-term beat-to-beat variability in
cardiovascular signals have not resolved the debate about the
completeness of linear analysis techniques. This paper further
evaluates the role of nonlinearities in short-term beat-to-beat
variability. We compared linear autoregressive moving average (ARMA)
and nonlinear neural network (NN) models for predicting instantaneous
heart rate (HR) and mean arterial blood pressure (BP) from past HR and
BP. To evaluate these models, we used HR and BP time series from the
MIMIC database. Experimental results indicate that NN-based
nonlinearities do not play a significant role and suggest that ARMA
linear analysis techniques provide adequate characterization of the
system dynamics responsible for generating short-term beat-to-beat
variability