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

被引:182
作者
Bauer, A
Kantelhardt, JW [1 ]
Bunde, A
Barthel, P
Schneider, R
Malik, M
Schmidt, G
机构
[1] Univ Halle Wittenberg, Fachbereich Phys, Halle, Germany
[2] Univ Halle Wittenberg, Zentrum Computat Nanosci, Halle, Germany
[3] Tech Univ Munich, Med Klin, D-8000 Munich, Germany
[4] Tech Univ Munich, Deutsch Herzzentrum, D-8000 Munich, Germany
[5] Univ Giessen, Inst Theoret Phys 3, Giessen, Germany
[6] St Georges Univ London, Dept Cardiac & Vasc Sci, London, England
关键词
time-series analysis; quasi-periodicities; non-stationary behaviour; synchronization; long-term correlations;
D O I
10.1016/j.physa.2005.08.080
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
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. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:423 / 434
页数:12
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