Phase-rectified signal averaging detects quasi-periodicities in non-stationary data

Axel Bauer, Jan W. Kantelhardt, Armin Bunde, Petra Barthel, Raphael Schneider, Marek Malik and Georg Schmidt

Physica A: Statistical Mechanics and its Applications, 2006, vol. 364, issue C, 423-434

Abstract: We present an efficient technique for the study of quasi-periodic oscillations in noisy, non-stationary signals, which allows the assessment of system dynamics despite phase resetting and noise. It is based on the definition of anchor points in the signal (in the simplest case increases or decreases of the signal) which are used to align (i.e., phase-rectify) the oscillatory fluctuations followed by an averaging of the surroundings of the anchor points. We give theoretical arguments for the advantage of the technique, termed phase-rectified signal averaging (PRSA), over conventional spectral analysis and show in a numerical test using surrogate heartbeat data that the threshold intensity for the detection of additional quasi-periodic components is approximately 75% lower with PRSA. With the use of different anchor point criteria PRSA is capable of separately analysing quasi-periodicities that occur during increasing or decreasing parts of the signal. We point to a variety of applications in the analysis of medical, biological, and geophysical data containing quasi-periodicities besides non-stationarities and 1/f noise.

Keywords: Time-series analysis; Quasi-periodicities; Non-stationary behaviour; Synchronization; Long-term correlations (search for similar items in EconPapers)
Date: 2006
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:364:y:2006:i:c:p:423-434

DOI: 10.1016/j.physa.2005.08.080

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