Title
Testing for nonlinearity in non-stationary physiological time series.
Abstract
Testing for nonlinearity is one of the most important preprocessing steps in nonlinear time series analysis. Typically, this is done by means of the linear surrogate data methods. But it is a known fact that the validity of the results heavily depends on the stationarity of the time series. Since most physiological signals are non-stationary, it is easy to falsely detect nonlinearity using the linear surrogate data methods. In this document, we propose a methodology to extend the procedure for generating constrained surrogate time series in order to assess nonlinearity in non-stationary data. The method is based on the band-phase-randomized surrogates, which consists (contrary to the linear surrogate data methods) in randomizing only a portion of the Fourier phases in the high frequency domain. Analysis of simulated time series showed that in comparison to the linear surrogate data method, our method is able to discriminate between linear stationarity, linear non-stationary and nonlinear time series. Applying our methodology to heart rate variability (HRV) records of five healthy patients, we encountered that nonlinear correlations are present in this non-stationary physiological signals.
Year
DOI
Venue
2011
10.1109/IEMBS.2011.6090734
EMBC
Keywords
Field
DocType
nonlinear time series analysis,nonlinearity testing,physiology,fourier phase,preprocessing ste,band phase randomized surrogate,nonstationary physiological time series,heart rate variability,linear surrogate data method,time series,domain analysis,time frequency analysis,correlation,time series analysis,high frequency,surrogate data,testing
Time series,Nonlinear system,Computer science,Fourier transform,Artificial intelligence,Surrogate data,Frequency domain,Computer vision,Algorithm,Speech recognition,Preprocessor,Correlation,Time–frequency analysis
Conference
Volume
ISSN
ISBN
2011
1557-170X
978-1-4244-4122-8
Citations 
PageRank 
References 
0
0.34
1
Authors
3
Name
Order
Citations
PageRank
Diego Guarín100.34
Edilson Delgado200.34
Álvaro Orozco302.03