Entropy Analysis of Heart Rate Variability in Different Sleep Stages

How the complexity or irregularity of heart rate variability (HRV) changes across different sleep stages and the importance of these features in sleep staging are not fully understood. This study aimed to investigate the complexity or irregularity of the RR interval time series in different sleep stages and explore their values in sleep staging. We performed approximate entropy (ApEn), sample entropy (SampEn), fuzzy entropy (FuzzyEn), distribution entropy (DistEn), conditional entropy (CE), and permutation entropy (PermEn) analyses on RR interval time series extracted from epochs that were constructed based on two methods: (1) 270-s epoch length and (2) 300-s epoch length. To test whether adding the entropy measures can improve the accuracy of sleep staging using linear HRV indices, XGBoost was used to examine the abilities to differentiate among: (i) 5 classes [Wake (W), non-rapid-eye-movement (NREM), which can be divide into 3 sub-stages: stage N1, stage N2, and stage N3, and rapid-eye-movement (REM)]; (ii) 4 classes [W, light sleep (combined N1 and N2), deep sleep (N3), and REM]; and (iii) 3 classes: (W, NREM, and REM). SampEn, FuzzyEn, and CE significantly increased from W to N3 and decreased in REM. DistEn increased from W to N1, decreased in N2, and further decreased in N3; it increased in REM. The average accuracy of the three tasks using linear and entropy features were 42.1%, 59.1%, and 60.8%, respectively, based on 270-s epoch length; all were significantly lower than the performance based on 300-s epoch length (i.e., 54.3%, 63.1%, and 67.5%, respectively). Adding entropy measures to the XGBoost model of linear parameters did not significantly improve the classification performance. However, entropy measures, especially PermEn, DistEn, and FuzzyEn, demonstrated greater importance than most of the linear parameters in the XGBoost model.300-s270-s.     

基于心率变异性的草原公路驾驶疲劳恢复调节方式

为研究草原地区驾驶疲劳恢复的特性,利用MP150型多导生理记录仪器收集驾驶员在疲劳恢复阶段不同调节方式下的心率变异性(heart rate variability, HRV)信号,结合主成分分析和均值、低高频均衡比和样本熵指标趋势分析,开展室内模拟驾驶疲劳恢复研究。结果表明：(1)音乐调节休息和车外自由活动方式下,驾驶员的疲劳状态表现为先加重再迅速恢复后波动的现象;(2)长距离驾驶后,不建议驾驶员立刻采用听音乐或下车活动方式调节疲劳,车内安静休息更适合驾驶员;(3)休息时间在20 min左右时,相较于车外自由活动,建议驾驶员采用音乐调节休息方式;休息时间超过20 min,驾驶员应采取多种方式调节驾驶疲劳。     

曲美他嗪对缺血性心肌病患者心率变异性的影向

目的:探讨曲美他嗪对缺血性心肌病患者心率变异性的影响.方法:选择60例缺血性心肌病患者,随机分为常规治疗组及曲美他嗪治疗组各30例,后者在常规治疗基础上加用曲美他嗪(20mg,3次/d),疗程24周.治疗前后通过动态心电图测定心率变异性(HRV)指标(SDNN、SDANN、rMSSD、PNN50、HF、LF、LF/HF...     

基于Poincaré散点图和符号动力学的心电分析方法

心率变异性（heartrate variability,HRV）可以用于进行心脏相关疾病的预测、预防和预后评价等.结合心电散点图和符号动力学的方法,从ECG信号中提取HRV序列,绘制心电散点图,并对散点图中散点进行分区编号编码.计算不同编码的出现概率进而计算整个序列信息熵.以该熵值作为心电特征用于识别和分类.实验得到窦性心律和房颤心律的分类正确率为86.67%,窦性心律与伴有失常心律的早搏分类正确率为90%.证明该方法能有效分类窦性心律与失常心律.      

不同海拔高度对学生心率变异性的影响

采用时域分析法、频域分析法对世居高原、亚高原、平原的90名高校非体育专业农村男学生进行心率变异性测试。结果表明:机体的交感神经调节功能随着海拔高度的增高呈现出先增强再降低的趋势;机体的副交感神经调节功能随着海拔高度的增高呈现出先降低再增高的趋势;机体自主神经的总体调节功能呈现出随着海拔高度增加而下降的趋势。     

Evaluation of mental fatigue based on multipsychophysiological parameters and kernel learning algorithms

Mental fatigue is an extremely sophisticated phenomenon, which is influenced by the environment, the state of health, vitality and the capability of recovery. A single parameter cannot fully describe it. In this paper, the effects of long time sustained low-workload visual display terminal （VDT） task on psychology are investigated by subjective self-reporting measures. Then power spectral indices of HRV, the P300 components based on visual oddball and wavelet packet parameters of EEG are combined to analyze the impacts of prolonged visual display terminal （VDT） activity on autonomic nervous system and central nervous system. Finally, wavelet packet parameters of EEG are extracted as the features of brain activity in different mental fatigue states. Kernel principal component analysis （KPCA） and support vector machine （SVM） are jointly applied to differentiate two states. The statistic results show that the level of both subjective sleepiness and fatigue increase significantly from pre-task to post-task, which indicate that the long time VDT task induces the mental fatigue to the subjects. The predominant activity of autonomic nervous system of subjects turns to the sympathetic activity from parasympathetic activity after the task. The P300 components and wavelet packet parameters of EEG are strongly related with mental fatigue. Moreover, the joint KPCA-SVM method is able to effectively reduce the dimensionality of the feature vectors, speed up the convergence in the training of SVM and achieve a high recognition accuracy （87%） of mental fatigue state. Multipsychophysiological measures and KPCA-SVM method could be a promising tool for the evaluation of mental fatigue.     

多尺度策略和替代数据检验——HRV时间不可逆性分析的两个要素

本文通过应用基于多尺度思想的（Pm,Gm）平面法和替代数据检验,对来自于不同人群以及来自于健康年轻人清醒、睡眠状态下的心率变异性（heartratevariability,HRV）进行了时间不可逆性分析．结果表明：健康成人的HRV普遍存在着时间不可逆性,而随着疾病的出现,这种不可逆性减弱但并非消失,大部分（超过75％）充血性心力衰竭患者的HRV仍具有时间不可逆性：健康年轻人的HRV不可逆性存在着昼夜节律和显著的昼夜差异,夜间睡眠时不可逆性更强．我们认为：由于产生HRV的心脏动力系统具有复杂的延迟特性,在对HRV进行时间不可逆分析时,为了得到更可靠的结论,建议采用多尺度策略以及进行替代数据检验．综合考虑上述两个因素的分析方法也较好地统一了已有报道的不同结论．     

心率变异的非线性特征参数估算

心率变异（Heart Rate Variability,HRV）是指人的心脏节律的微小变动量，与人的健康状态和精神状态直接相关，具有明显的非线性特征。在本文中，对HRV时间序列的几个非线性特征参数进行估算．从而对心脏健康状态（心率正常）与非健康状态（心率变异）HRV之间的差别进行比较。首先利用小波变换技术对心电信号（ECG）数据进行R波的准确定位，经过重采样得到HRV序列。关联维的计算结果表明，健康状态和非健康状态HRV时间序列具有不同的分形结构，在相空间重构的基础上对HRV进行最大李雅普诺夫指数的估算。结果表明，健康状态和非健康状态HRV时间序列的最大李雅普诺夫指数均为正值，但处于心率不齐状态的节律的混沌程度明显低于健康状态，健康状态HRV的复杂度要高于非健康状态HRV的复杂度，近似嫡和复杂度的分析结果基本相似，健康状态HRV的近似熵要高于非健康状态HRV的近似熵。利用这些非线性特征参数对健康状态和非健康状态的HRV进行比较分析，可以为诊断提供依据，并对深入了解生命规律有潜在价值     

运动训练对心脏植物神经功能的影响

随着运动训练的进行,心脏植物神经功能会最为敏感地产生反应和适应,而应用心率变异性(HRV)分析方法可有效评价人体心脏植物神经功能。通过对篮球专项运动系和普通大学生各16名进行安静态心率变异性的时域和频域分析,观察篮球运动对心脏植物神经功能的影响,掌握运动员的身体机能状况。     

汽车驾驶员疲劳状态下穴位磁刺激效应分析

在驾驶员疲劳状态下，应用心率变异性(HRV)功率谱分析，评价穴位碰刺激对自主神经系统功能的调整作用．健康志愿人员26名，每人参加两组模拟驾驶实验，A组为磁灸组，B组为对照组，时间均为90min．对磁灸组志愿者，在执行驾驶任务1h后，施加磁刺激30min．实验过程中实时记录实验者心电信号．执行任务过程中，实验者心率变异性表现出明显的线性趋势．磁灸组施加穴位磁刺激后，实验者表现为交感神经活动性降低，迷走神经活动性提高，精神紧张及疲劳程度降低．穴位磁刺激有利于改善心脏自主神经系统功能状态，可在一定程度上缓解精神疲劳．