睡眠时相与心率变异性的关系研究  

Research on the Relationship between Sleep Phases and Heart Rate Variability

作　　者：江丽仪[1] 吴效明[1] 

机构地区：[1]华南理工大学生物医学工程系,广州510006

出　　处：《生物医学工程学杂志》2011年第1期148-152,共5页Journal of Biomedical Engineering

基　　金：广东省科技计划资助项目(2009B030801004)

摘　　要：睡眠时相研究是评估人体睡眠状态和睡眠质量的重要环节。本文采用去趋势波动分析(DFA)和自回归模型谱分析对45名健康者的睡眠RR间期(RRI)序列进行研究,从参数的变化规律中寻找心率变异性(HRV)与睡眠时相的对应关系。实验结果表明,在不同的睡眠时相,RRI序列都存在长程相关性。随着睡眠加深,DFA的标定指数逐渐减小,而功率谱参数显示副交感神经活动占主导。比较两种方法判断睡眠时相的结果,DFA的标定指数比功率谱参数更有统计学意义,这将为利用HRV判别睡眠时相提供新的技术手段。The study of sleep phases is helpful to evaluate the sleep state and quality.In order to explore the relationship between heart rate variability（HRV） and sleep phases,detrended fluctuation analysis（DFA） and autoregressive（AR） model spectrum estimation were used to analyze R-R interval（RRI） sequence of 45 healthy subjects from Sleep Heart Rate and Stroke Volume Data Bank.The results show that,in different sleep phases,long-range correlation was detected in RRI sequence.From rapid eye movement to light sleep and deep sleep,scaling exponent α1 and α2 were decreasing,while spectral parameters LFn.u.,HFn.u.and LF/HF showed increasing parasympathetic activity.Scaling exponents had more significant differences than spectral parameters in distinguishing different sleep phases.Thus,DFA will be a better analysis method to quantify HRV in different sleep stages.

关 键 词：睡眠时相 心率变异性 去趋势波动分析 自回归模型谱估计 

分 类 号：R740[医药卫生—神经病学与精神病学]