Communications Technology Group, Aragón Institute of Engineering Research (I3A), University of Zaragoza, M de Luna 1, Zaragoza 50018, Spain.
Physiol Meas. 2012 Mar;33(3):315-31. doi: 10.1088/0967-3334/33/3/315. Epub 2012 Feb 22.
In this study, a framework for the characterization of the dynamic interactions between RR variability (RRV) and systolic arterial pressure variability (SAPV) is proposed. The methodology accounts for the intrinsic non-stationarity of the cardiovascular system and includes the assessment of both the strength and the prevalent direction of local coupling. The smoothed pseudo-Wigner-Ville distribution (SPWVD) is used to estimate the time-frequency (TF) power, coherence, and phase-difference spectra with fine TF resolution. The interactions between the signals are quantified by time-varying indices, including the local coupling, phase differences, time delay, and baroreflex sensitivity (BRS). Every index is extracted from a specific TF region, localized by combining information from the different spectra. In 14 healthy subjects, a head-up tilt provoked an abrupt decrease in the cardiovascular coupling; a rapid change in the phase difference (from 0.37 ± 0.23 to -0.27 ± 0.22 rad) and time delay (from 0.26 ± 0.14 to -0.16 ± 0.16 s) in the high-frequency band; and a decrease in the BRS (from 23.72 ± 7.66 to 6.92 ± 2.51 ms mmHg(-1)). In the low-frequency range, during a head-up tilt, restoration of the baseline level of cardiovascular coupling took about 2 min and SAPV preceded RRV by about 0.85 s during the whole test. The analysis of the Eurobavar data set, which includes subjects with intact as well as impaired baroreflex, showed that the presented methodology represents an improved TF generalization of traditional time-invariant methodologies and can reveal dysfunctions in subjects with baroreflex impairment. Additionally, the results also suggest the use of non-stationary signal-processing techniques to analyze signals recorded under conditions that are usually supposed to be stationary.
在这项研究中,提出了一种用于描述 RR 变异性 (RRV) 和收缩压变异性 (SAPV) 之间动态相互作用的框架。该方法考虑了心血管系统的固有非平稳性,并包括评估局部耦合的强度和主要方向。采用平滑伪魏格纳-维尔分布 (SPWVD) 以精细的时频 (TF) 分辨率估计时频 (TF) 功率、相干性和相位差谱。通过时变指数来量化信号之间的相互作用,包括局部耦合、相位差、时滞和压力反射敏感性 (BRS)。每个指数都是从特定的 TF 区域中提取出来的,通过结合不同谱的信息来局部化该区域。在 14 名健康受试者中,头高位倾斜会引起心血管耦合的突然下降;高频带中的相位差(从 0.37 ± 0.23 变为 -0.27 ± 0.22 rad)和时滞(从 0.26 ± 0.14 变为 -0.16 ± 0.16 s)快速变化;BRS(从 23.72 ± 7.66 变为 6.92 ± 2.51 ms mmHg(-1)) 降低。在低频范围内,在头高位倾斜期间,心血管耦合的基线水平恢复大约需要 2 分钟,并且在整个测试过程中,SAPV 比 RRV 提前约 0.85 s。对包括压力反射正常和受损的 Eurobavar 数据集的分析表明,所提出的方法代表了传统时不变方法的改进 TF 推广,并且可以揭示压力反射受损受试者的功能障碍。此外,结果还表明,在通常被认为是静止的条件下记录的信号中,可以使用非平稳信号处理技术来分析信号。