基于有限穿越水平可视图的短时睡眠心率变异性研究

发布时间：2018-01-09 15:08

本文关键词：基于有限穿越水平可视图的短时睡眠心率变异性研究　出处：《物理学报》2017年16期 　论文类型：期刊论文

【摘要】：心率数据是最易于获取的人体生理数据之一,基于心率变异性的睡眠分析是近年来各种用于日常健康管理的可穿戴设备功能的一个重要发展方向,需要不断探索可以应用于标准睡眠分期时间窗(约30 s)的各类短时特征参数.利用近期报道的有限穿越水平可视图,并进一步提出一种加权有限穿越水平可视图,将不同睡眠状态下的短时心率变异序列映射为网络,进而提取平均集聚系数、特征路径长度、集聚系数熵、路径分布熵、加权集聚系数熵和加权路径分布熵等网络特征参数进行统计分析.结果表明,各网络参数值在醒觉、浅睡期、深睡期和快速眼动期的幅度水平具有显著差异,体现了所述方法在基于短时心率变异数据的睡眠分期中的有效性.同时,进一步研究了健康年轻人和中老年人在不同睡眠状态下的网络参数值,发现两者虽然存在整体的水平差异,但是在不同睡眠状态间的变化仍具有相同的趋势,反映出相对于正常的年龄老化,睡眠调制对心脏动力学系统具有更显著的影响,也说明所述方法可作为基于心率变异性的睡眠研究的一种新的辅助工具.
[Abstract]:Heart rate data is one of the most easily available physiological data of human body. Sleep analysis based on heart rate variability is an important development direction of wearable devices for daily health management in recent years. There is a need to explore all kinds of short-term feature parameters that can be applied to the standard sleep stage time window (about 30 s). Furthermore, a weighted finite traversing horizontal visual map is proposed, which maps short time heart rate variability series under different sleep states into a network, and then extracts the average aggregation coefficient, characteristic path length, and aggregation coefficient entropy. The network characteristic parameters such as path distribution entropy, weighted aggregation coefficient entropy and weighted path distribution entropy are statistically analyzed. The results show that the network parameters are in wake up and shallow sleep period. There were significant differences in amplitude levels between deep sleep and rapid eye movements, which demonstrated the effectiveness of the method in sleep stages based on short term HRV data. At the same time. The network parameters of healthy young people and middle aged people in different sleep states were further studied. It was found that the changes of network parameters in different sleep states still had the same trend although there was an overall level difference between them. It reflects that sleep modulation has a more significant effect on cardiac dynamic system than that of normal aging. It also shows that the proposed method can be used as a new assistant tool for sleep research based on heart rate variability.
【作者单位】：常熟理工学院物理与电子工程学院;南京大学电子科学与工程学院生物医学电子工程研究所;
【基金】：江苏省高校自然科学研究项目(批准号:15KJD310002) 国家自然科学基金(批准号:61402057) 江苏省高校优秀中青年教师和校长境外研修计划(2016年度)资助的课题~~
【分类号】：O157.5;R740
【正文快照】： 1引言睡眠是一种重要的生理活动,对于人体的物理和精神方面的自我恢复具有非常关键的作用[1].根据美国睡眠医学学会(American Academy of SleepMedicine,AASM)发布的规范,睡眠过程可以进行分期,具体分为醒觉(wakefulness,W),非快速眼动期(non-rapid eye movement,NREM)和快速

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