Dresden 2006 – wissenschaftliches Programm
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DY: Dynamik und Statistische Physik
DY 43: Signals and neuronal Networks
DY 43.3: Vortrag
Donnerstag, 30. März 2006, 12:00–12:15, SCH 251
Phase-Rectified Signal Averaging Detects Quasi-Periodicities in Non-Stationary Data — •J. W. Kantelhardt1, A. Bauer2, A. Bunde3, P. Barthel2, R. Schneider2, M. Malik4, and G. Schmidt2 — 1Fachber. Physik u. Zentr. f. Computational Nanoscience, Martin-Luther-Universität, Halle (Saale), Germany — 2Med. Klinik u. Dt. Herzzentrum der Technischen Universität München, Germany — 3Inst. f. Theoretische Physik III, Justus-Liebig-Universität, Giessen, Germany — 4Dept. of Cardiac and Vascular Sciences, St. George’s, University of London, UK
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.