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一种使用连续小波变换分析呼吸性窦性心律不齐的方法。

A method for the analysis of respiratory sinus arrhythmia using continuous wavelet transforms.

作者信息

Cnockaert Laurence, Migeotte Pierre-François, Daubigny Lise, Prisk G Kim, Grenez Francis, Sá Rui Carlos

机构信息

Faculté des Sciences Appliquées, Université Libre de Bruxelles, 1050 Brussels, Belgium.

出版信息

IEEE Trans Biomed Eng. 2008 May;55(5):1640-2. doi: 10.1109/TBME.2008.918576.

Abstract

A continuous wavelet transform-based method is presented to study the nonstationary strength and phase delay of the respiratory sinus arrhythmia (RSA). The RSA is the cyclic variation of instantaneous heart rate at the breathing frequency. In studies of cardio-respiratory interaction during sleep, paced breathing or postural changes, low respiratory frequencies, and fast changes can occur. Comparison on synthetic data presented here shows that the proposed method outperforms traditional short-time Fourier-transform analysis in these conditions. On the one hand, wavelet analysis presents a sufficient frequency-resolution to handle low respiratory frequencies, for which time frames should be long in Fourier-based analysis. On the other hand, it is able to track fast variations of the signals in both amplitude and phase for which time frames should be short in Fourier-based analysis.

摘要

提出了一种基于连续小波变换的方法来研究呼吸性窦性心律不齐(RSA)的非平稳强度和相位延迟。RSA是呼吸频率下瞬时心率的周期性变化。在睡眠、定频呼吸或姿势变化期间的心肺相互作用研究中,可能会出现低呼吸频率和快速变化。此处给出的合成数据比较表明,在这些条件下,所提出的方法优于传统的短时傅里叶变换分析。一方面,小波分析具有足够的频率分辨率来处理低呼吸频率,而在基于傅里叶的分析中,处理低呼吸频率时时间帧应该较长。另一方面,它能够跟踪信号在幅度和相位上的快速变化,而在基于傅里叶的分析中,处理信号的快速变化时时间帧应该较短。

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