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被动倾斜试验中的心率变异性:自回归和快速傅里叶变换频谱分析的比较评估

Heart rate variability in passive tilt test: comparative evaluation of autoregressive and FFT spectral analyses.

作者信息

Badilini F, Maison-Blanche P, Coumel P

机构信息

Department of Cardiology, Hôpital Lariboisière, Paris, France.

出版信息

Pacing Clin Electrophysiol. 1998 May;21(5):1122-32. doi: 10.1111/j.1540-8159.1998.tb00159.x.

Abstract

The dynamic response of the autonomic nervous system during tilting is assessed by changes in the low (LF) and high frequency (HF) components of the RR series power spectral density (PSD). Although results of many studies are consistent, some doubts related to different methodologies remain. Specifically, the respective relevance of autoregressive (AR) and fast Fourier transform (FFT) methods is often questioned. Beat-to-beat RR series were recorded during 90 degrees passive tilt in 18 healthy subjects (29 +/- 5 years, eight females). FFT-based (50% overlap, Hanning window) and AR-based (Levinson-Durbin algorithm) PSDs were calculated on the same RR intervals. Powers in very low frequency (VLF: < 0.04 Hz), LF (0.04-0.15 Hz), and HF (0.15-0.40 Hz) bands were calculated either by spectrum integration (FFT and ARIN), by considering the highest AR component in each band (ARHP), or by summation of all AR components (ARAP). LF and HF raw powers (ms2) were normalized by total power (%P) and by total power after removal of the VLF component (nu). AR and FFT total powers were not different, regardless of body position. In supine condition, when compared to ARHP and ARAP, FFT underestimated VLF and overestimated LF, whereas in tilt position FFT overestimated HF and underestimated LF. However, supine/tilt trends were consistent in all methods showing a clear reduction of HF and a less marked increase of LF. Both normalization procedures provided a significant LF increase and further magnified the HF decrease. Results obtained with ARIN were remarkably close to those obtained with FFT. In conclusion, significant differences between AR and FFT spectral analyses do exist, particularly in supine position. Nevertheless, dynamic trends provided by the two approaches are consistent. Normalization is necessary to evidence the LF increase during tilt.

摘要

通过RR间期功率谱密度(PSD)的低频(LF)和高频(HF)成分变化来评估自主神经系统在倾斜过程中的动态反应。尽管许多研究结果是一致的,但关于不同方法仍存在一些疑问。具体而言,自回归(AR)和快速傅里叶变换(FFT)方法各自的相关性经常受到质疑。在18名健康受试者(29±5岁,8名女性)进行90度被动倾斜期间记录逐搏RR间期。基于FFT(50%重叠,汉宁窗)和基于AR(莱文森 - 杜宾算法)的PSD在相同的RR间期上计算。极低频(VLF:<0.04 Hz)、LF(0.04 - 0.15 Hz)和HF(0.15 - 0.40 Hz)频段的功率通过频谱积分(FFT和ARIN)、考虑每个频段中最高的AR成分(ARHP)或所有AR成分的总和(ARAP)来计算。LF和HF原始功率(ms²)通过总功率(%P)以及去除VLF成分后的总功率(nu)进行归一化。无论身体位置如何,AR和FFT总功率没有差异。在仰卧位时,与ARHP和ARAP相比,FFT低估了VLF并高估了LF,而在倾斜位时FFT高估了HF并低估了LF。然而,所有方法中仰卧位/倾斜位的趋势是一致的,显示出HF明显降低,LF增加不明显。两种归一化程序都使LF显著增加,并进一步放大了HF的降低。用ARIN获得的结果与用FFT获得的结果非常接近。总之,AR和FFT频谱分析之间确实存在显著差异,特别是在仰卧位。然而,两种方法提供的动态趋势是一致的。归一化对于证明倾斜期间LF增加是必要的。

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