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利用心电图RR间期的洛伦兹图估计入睡期的睡眠阶段。

Estimation of sleep stage in the falling asleep period using a Lorenz plot of ECG RR intervals.

作者信息

Hagiwara Hiroshi

机构信息

Department of Human and Computer Intelligence, College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Shiga 525-8577, Japan.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:2510-3. doi: 10.1109/IEMBS.2009.5334854.

Abstract

The falling asleep period is the shift from the waking stage to sleep stages 1 and 2. Changes during the falling asleep period can be observed on electroencephalograms (EEGs). In this research, we developed a technique for estimating sleep stage at the falling asleep period without using EEGs. We performed a Lorenz plot (LP) using the intervals between heartbeats, known as electrocardiogram (ECG) RR intervals, of the falling asleep period, and confirmed that changes in the distribution on the LP occur according to changes in sleep stage. To evaluate the changes in these distributions, we projected the LP on y = x axis and y = -x axis, and analyzed the shifting of mean and standard deviation in each sleep stage. The results demonstrated that the distance from the coordinate origin to the mean of distribution became longer as sleep stage deepened, but the variations in the distribution of the LP stabilized. By quantitatively evaluating these phenomena, we proposed two indices of mean (M of LP) and ellipse area (S of LP) of the falling asleep period. Additionally, a multiple regression analysis was done to calculate sleep stage quantitatively, culminating in the derivation of the estimated equation of falling asleep period. Therefore, we could easily estimate the directionality of the sleep stage at the falling asleep period using a LP of ECG RR intervals.

摘要

入睡期是从清醒阶段向睡眠1期和2期的转变。入睡期的变化可以在脑电图(EEG)上观察到。在本研究中,我们开发了一种不使用EEG来估计入睡期睡眠阶段的技术。我们利用入睡期心跳间隔(即心电图(ECG)RR间期)进行了洛伦兹图(LP)分析,并证实LP上分布的变化会随着睡眠阶段的变化而发生。为了评估这些分布的变化,我们将LP投影到y = x轴和y = -x轴上,并分析了每个睡眠阶段均值和标准差的变化情况。结果表明,随着睡眠阶段加深,从坐标原点到分布均值的距离变长,但LP分布的变化趋于稳定。通过对这些现象进行定量评估,我们提出了入睡期的均值(LP的M)和椭圆面积(LP的S)这两个指标。此外,还进行了多元回归分析以定量计算睡眠阶段,最终得出了入睡期的估计方程。因此,我们可以通过ECG RR间期的LP轻松估计入睡期睡眠阶段的方向性。

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