Phase-rectified signal averaging detects quasi-periodicities in non-stationary data
Phase-rectified signal averaging detects quasi-periodicities in non-stationary data
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DOI：
10.1016/j.physa.2005.08.080
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发表时间：
2006-05-15
影响因子：
3.3
通讯作者：
Schmidt, G
中科院分区：
文献类型：
--
作者：
Bauer, A;Kantelhardt, JW;Schmidt, G
我们提出了一种有效的技术来研究噪声、非平稳信号中的准周期振荡，该技术允许在不考虑相位重置和噪声的情况下评估系统动力学。它基于信号中的锚点的定义(在最简单的情况下，信号的增加或减少)，这些锚点被用来对准(即，相位校正)随后的锚点周围的平均的振荡波动。我们从理论上论证了相位校正信号平均(PRSA)技术相对于传统频谱分析的优势，并在使用替代心跳数据的数值测试中表明，使用PRSA检测额外的准周期分量的阈值强度大约降低75%。通过使用不同的锚点准则，PRSA能够单独分析在信号的增加或减少部分期间发生的准周期。我们指出了在医学、生物和地球物理数据分析中的各种应用，这些数据除了具有非平稳性和1/f噪声外，还包含准周期。(C)2005 Elsevier B.V.保留所有权利。
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.