通过动态分析方法捕捉心率变异性的瞬时变化

Toward Capturing Momentary Changes of Heart Rate Variability by a Dynamic Analysis Method.

作者信息

Zhang Haoshi, Zhu Mingxing, Zheng Yue, Li Guanglin

机构信息

The Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, Guangdong, PR China.

出版信息

PLoS One. 2015 Jul 14;10(7):e0133148. doi: 10.1371/journal.pone.0133148. eCollection 2015.

Abstract

The analysis of heart rate variability (HRV) has been performed on long-term electrocardiography (ECG) recordings (1224 hours) and short-term recordings (25 minutes), which may not capture momentary change of HRV. In this study, we present a new method to analyze the momentary HRV (mHRV). The ECG recordings were segmented into a series of overlapped HRV analysis windows with a window length of 5 minutes and different time increments. The performance of the proposed method in delineating the dynamics of momentary HRV measurement was evaluated with four commonly used time courses of HRV measures on both synthetic time series and real ECG recordings from human subjects and dogs. Our results showed that a smaller time increment could capture more dynamical information on transient changes. Considering a too short increment such as 10 s would cause the indented time courses of the four measures, a 1-min time increment (4-min overlapping) was suggested in the analysis of mHRV in the study. ECG recordings from human subjects and dogs were used to further assess the effectiveness of the proposed method. The pilot study demonstrated that the proposed analysis of mHRV could provide more accurate assessment of the dynamical changes in cardiac activity than the conventional measures of HRV (without time overlapping). The proposed method may provide an efficient means in delineating the dynamics of momentary HRV and it would be worthy performing more investigations.

摘要

心率变异性(HRV)分析已在长期心电图(ECG)记录(12至24小时)和短期记录(2至5分钟)上进行,这些记录可能无法捕捉HRV的瞬间变化。在本研究中,我们提出了一种分析瞬间HRV(mHRV)的新方法。将ECG记录分割为一系列重叠的HRV分析窗口,窗口长度为5分钟,时间增量不同。利用合成时间序列以及来自人类受试者和犬类的真实ECG记录上的四种常用HRV测量时间过程,评估了所提方法在描绘瞬间HRV测量动态方面的性能。我们的结果表明,较小的时间增量可以捕捉到更多关于瞬态变化的动态信息。考虑到过短的增量(如10秒)会导致这四种测量的时间过程出现凹陷,本研究建议在mHRV分析中采用1分钟的时间增量(4分钟重叠)。使用来自人类受试者和犬类的ECG记录进一步评估了所提方法的有效性。初步研究表明,与传统的HRV测量方法(无时间重叠)相比,所提的mHRV分析能够更准确地评估心脏活动的动态变化。所提方法可能为描绘瞬间HRV的动态提供一种有效手段,值得进行更多研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/00cc/4501678/00750eb22cf7/pone.0133148.g001.jpg

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