基于心率变异分析的睡眠分期方法

利用隐马尔可夫模型（HMM）对心率变异性（HRV）进行分析，识别HRV在不同睡眠分期的模式变化，从而推算出相应的睡眠分期。在信号处理的过程中采取了一定的措施降低个体差异对分析的影响；在特征提取中还考虑了HRV中超低频分量和睡眠的关系。由于心率信号的提取对睡眠几乎没有任何干扰，因此，本文提出的睡眠分期方法可以较好地反映受试者在自然条件下真实的睡眠状况，实验证明，该方法简单可行，其睡眠分期的结果和人工分期相比的符合率可以满足很多睡眠监测场合的需要，尤其适用于健康人常年的睡眠监测。     

基于多特征融合的睡眠分期

目的 为了有效实现睡眠自动分期,对睡眠障碍等相关疾病的诊断提供更多依据,本文提出了一种基于多特征融合的睡眠分期方法.方法 数据来自ISRUC-Sleep数据库,首先对10名健康受试者和10名睡眠障碍患者的脑电(electroencephalogram,EEG)信号计算3种特征——样本熵、小波包能量和去趋势波动.然后采用支持向量机(support vector machine,SVM)构建睡眠分期模型,并验证该模型的准确性.此外,为了进行比较加入心电(electrocardiogram,ECG)和肌电(electromyogram,EMG)通道.结果 健康受试者和睡眠障碍患者睡眠分期的准确率分别达到87.4％和86.3％.结论 基于多特征融合的睡眠分期方法能够有效地提高睡眠分期的准确率.     

R-R间期分析与睡眠分期

研究心脏节律与睡眠结构之间的关系。以MIT/BIH睡眠数据库记录的R -R间期为分析对象 ,采用典型的心率变异分析方法以及计算RRI序列的平均频率、搏间自相关系数、LZ复杂度 ,将结果与数据库中睡眠分期标注进行比对。结果显示时域、频域及非线性分析从不同角度、不同程度上反映了心率变异与睡眠分期之间的联系 ,并且有些方法能较好地表达睡眠状态的变迁。本文结果有助于利用多生理参数研究睡眠分期。     

基于心率变异性的自动睡眠分期及其脑电图验证

睡眠障碍会严重影响人们的日常生活,因此睡眠的早期监测对睡眠疾病的预防和诊断有重要意义。采用自行研制的便携式多导睡眠监护仪,开展了103人次的居家夜间睡眠数据收集(含脑电、眼电、肌电和心电信号)。然后,从同步采集的心电数据RR间期中提取时域、频率和非线性特征,组合出最高达426个心率变异性(HRV)特征,基于Xgboost算法构建模型对睡眠中的清醒期(wake)、非快速眼动|期(N1)、非快速眼动Ⅱ期(N2)、非快速眼动Ⅲ期(N3)和快速眼动期(REM)进行五分类(wake、N1、N2、N3、REM)、三分类(wake+N1、REM、N2+N3)和二分类(wake、N1+N2+N3+REM)预测,并与脑电图睡眠分期标签进行验证。最后,五分类、三分类和二分类测试结果准确率分别达到84.0%、89.1%和95.2%,F1-score达到83.2%、88.9%和94.9%,为同类模型研究中表现最佳。说明HRV与睡眠阶段具有良好的相关性,基于便携式设备收集数据构建的算法模型可以较好地识别睡眠状态。     

基于心率变异性分析的睡眠分期算法研究和验证

为实现睡眠分期,为穿戴式生理参数监测技术在慢病监测领域的应用提供技术支撑,发展基于心率变异性和支持向量机模型的睡眠分期算法。从心率时间间期序列中提取时域、频域和非线性等86个特征,将多导睡眠图仪的三分类结果(醒、快速眼动期、非快速眼动期)作为“金标准”,采用支持向量机作为多分类器模型;为保证训练集数据质量,使用开放睡眠数据库SHHS中由专家确认挑选的67例PSG样本作为训练集,实现特征筛选和模型参数训练。为验证模型的泛化性能,从SHHS数据库中进一步随机提取939例PSG样本,对模型性能进行测试。睡眠分期模型在训练集上的五折交叉验证的准确率为84.00%±1.33%,卡帕系数为0.70±0.03;在939例测试集上的准确率为76.10%±10.80%,卡帕系数为0.57±0.15。剔除RR间期异常(110例)和明显睡眠结构异常(29例)的样本后,测试集(800例)的准确率为82.00%±5.60%,卡帕系数为0.67±0.14。所提出的基于心率变异性分析的睡眠分期算法具有较高的准确性,大样本人群测试结果表明,该模型具有较好的普适性。     

基于复杂性测度的睡眠脑电分期处理方法研究

提高临床脑部及神经系统疾病的早期诊断水平,及时予以控制和治疗,是降低脑疾病对人类危害最有效的途径。探讨复杂性测度在睡眠脑电分期中的应用,主要利用加窗的Lempel-Ziv复杂度处理算法对经采用小波变换滤波算法滤除生理干扰后的睡眠脑电信号进行分期处理,并与没有加窗的Lempel-Ziv复杂度处理算法的仿真处理结果进行比较。结果表明：加窗的Lempel-Ziv复杂度算法能更好地将睡眠脑电不同状态分开,在一定程度上减少由脑电的非平稳性带来的计算上的片面性,同时兼顾各期睡眠脑电状态的不均匀性,在很大程度上满足临床的应用要求。     

应用近似熵对睡眠脑电进行分期的研究

主要介绍了一种新的度量序列复杂性的统计方法－近似熵（ＡｐＥｎ）并将其于睡眠脑电的研究，提取出各睡眠期的近似熵特征，实验结果显示，从清醒期到ＮＲＥＭ期的Ⅲ，Ⅳ期，近似熵由最大依次减小，到ＲＥＭ期又回以接近，Ｉ，Ⅱ期，根据这一特征对睡眠脑电进行分期实验，得到良好的效果，说明近似熵是一种值得重视的，很有前景的复杂度度量方法。     

抑郁症、原发性失眠睡眠脑电生理特征的对照研究

目的:探讨抑郁症、原发性失眠睡眠脑电生理特征的异同点。方法:对25例抑郁症、15例原发性失眠和14例正常人进行多导睡眠的对照研究。结果:抑郁症和原发性失眠在睡眠潜伏期(SL)、睡后觉醒次数(AN)、觉醒总时间(AT)、觉睡比(AT/TST%)方面均较正常对照组长(或高)(P0.01),在睡眠总时间(TST)、睡眠效率(SE)、睡眠维持率(SM)S1、S2时间方面均较正常对照组短(或低)(P0.05);抑郁症在REM活动度(RA)、REM活动强度(RI)、REM活动密度(RD)、第一个REM时间(FRT)、REM出现次数(RSN)等方面均较原发性失眠长(或高)(P0.01);原发性失眠在REM时间(RT)、REM百分比(RT%)方面差异非常显著低于抑郁症(P0.01),在REM潜伏期(RL)、睡后觉醒次数(AN)显著高于抑郁症(P0.05)。结论:抑郁症和原发性失眠患者均存在一定特征性的睡眠异常,抑郁症与原发性失眠的快波睡眠特征有差异。     

基于注意力机制与双向门控循环单元的多导睡眠图睡眠阶段分期方法研究

多导睡眠图(PSG）监测是临床上用于诊断诸如失眠、呼吸暂停等疾病的重要手段。为了解决以手工逐帧视觉判断PSG进行睡眠障碍患者睡眠阶段分期耗时长、耗费精力大等问题,本文提出一种结合卷积神经网络（CNN）与双向门控循环神经网络（Bi GRU）的深度学习算法模型,并设计了一种动态稀疏性自注意力机制以解决门控循环单元（GRU）网络对长距离信息难以获得准确向量表示的问题。本文采集来自上海精神卫生中心143例睡眠障碍患者整晚PSG数据并结合开源数据集153例睡眠障碍患者整晚PSG数据,选取其中的6个脑电（EEG）信号通道、2个眼电（EOG）信号通道与单个下颌肌电（EMG）信号通道等共9个通道的电生理通道信号进行模型训练与测试评估。经交叉验证后得到的分期准确率为（84.0±2.0）%,一致性检验值为0.77±0.50,优于医师间评分的一致性检验值0.75±0.11。实验结果表明,本文算法模型在不同人群中具有较高的分期效果并具有普适性,对于协助临床医师进行快速、大规模PSG睡眠自动分期具有重要研究意义。     

大学生人格特征及社会适应与睡眠障碍的关系

目的：探讨大学生人格特征及社会适应与睡眠障碍的关系,为睡眠的心理健康教育和心理干预提供参考。方法：采用匹兹堡睡眠质量指数量表（PSQI）、艾森克人格问卷（EPQ）、社会适应性自评问卷对4548名大学生进行问卷调查。结果：19．8％的大学生存在睡眠障碍;睡眠障碍组EPQ的P分、N分显著高于睡眠正常组（ t＝－8．234,－21．274;P＞0．001）,E分、L分和社会适应性显著低于睡眠正常组（t＝9．077,7．855,9．379;P＜0．001）;PSQI总分、EPQ各维度及社会适应性之间均呈显著相关（P＜0．001）。结论：为数不少的大学生存在睡眠障碍,睡眠障碍的大学生具有情绪不稳、偏内向、有一定精神质倾向且社会成熟度偏低等人格特征存在一定的社会适应问题。睡眠障碍、人格特征与社会适应相互影响,相互作用。建议学校心理健康教育和心理干预要注重从调整和塑造个性行为、提高社会适应能力等方面,改善大学生的睡眠障碍问题。     

基于谱分析方法提取心动周期变异性中的睡眠结构信息

利用心动周期的谱分析方法 ,充分挖掘了心动周期变异性中与脑电睡眠分期信息相关的特征参数 ,并利用主成分分析法去除掉了特征之间的相关性 ,最后利用基于 Fisher分类准则的决策树分别建立了健康人和睡眠呼吸暂停低通气综合症病人的睡眠分期全自动识别模型。试验结果表明 ,该模型准确性好 ,鲁棒性强     

Heart Rate Preceding Motility in Sleep

Spontaneous movements in both stage 2 and REM steep are preceded by similar heart rate increase, beginning approximately 8 sec before onset the movement. It is suggested that the HR acceleration before spontaneous movement in sleep is not a gradual response to vascular congestion but, rather, may be triggered by internal arousal stimuli which, like movements, have sleep-stage-specific rules of occurrence.     

多分辨分析提取心率变异性中的睡眠结构信息

本文从工程分析的角度探索通过分析心率变异性推知健康人夜间睡眠结构的可行性、针对心率变化在睡眠过程中的特点,对心动间期信号作基于小波变换的多分辨率分析,深入考察了不同睡眠时相中的RRV(R-R interval variability)多分辨率信号,尤其在睡眠时相转换时的变化特点.建立了关于健康人睡眠规律和睡眠RR规律的规则库.综合分析RRV在多分辨率下的信息,用模糊逻辑推理系统对某时间段不同睡眠时相的隶属度进行推理.经对26例健康人睡眠RRV分析,与脑电人工分析结果比较,睡眠基本结构的平均符合率达到85%,醒觉和睡眠状态的平均符合率达到93%,证明用本方法进行睡眠结构分析是可行的.     

Comparison of Respiratory Rates Derived from Heart Rate Variability, ECG Amplitude, and Nasal/Oral Airflow

It would often be desirable to obtain the respiratory rate during everyday conditions without obtaining an additional respiratory trace. This study investigates the agreement between respiratory rate assessed from the electrocardiogram (ECG) and the reference respiratory rate derived from a nasal/oral airflow (AF). Nasal/oral airflow and a Holter ECG were recorded in 52 healthy subjects (26 males, age range: 25.4–85.4 years) during everyday conditions for at least 10 h, including night-time sleep. The respiratory rate was assessed for each 5-min epoch (1) using respiratory sinus arrhythmia (RSA), (2) utilizing the respiration induced variations of the R-wave amplitude (ECG derived respiration (EDR)). The agreement with respect to AF was quantified using the average/std and the concordance correlation coefficient ρ_c. For RSA and EDR the difference with respect to AF was 0.2 cpm (std: 0.6 cpm) during sleep and −0.2 cpm (std: 1.0 cpm) during wake time. During sleep the RSA-approach performed best for subjects ≤50 years (ρ_c = 0.79) and worst for subjects >50 years (ρ_c = 0.41). The correlation of the EDR-approach was ρ_c = 0.73 for both groups. In conclusion, the respiratory rate may be assessed with reasonable agreement by both methods in younger subjects, but EDR should be preferred in the elderly.

Blood Pressure and Heart Rate During Continuous Experimental Sleep Fragmentation in Healthy Adults

Study Objectives:

This paper aims to determine whether experimental arousals from sleep delay the sleep related fall in cardiovascular activity in healthy adults.

Design:

We report the results of 2 studies. The first experiment manipulated arousals from sleep in young adults. The second compared the effect of frequent arousals on young and middle-aged adults. The influence of arousals were assessed in 2 ways; (1) the fall in cardiovascular activity over sleep onset and the early sleep period, and (2) the underlying sleep levels during the sleep periods in between arousals.

Setting:

Both experiments were conducted in the sleep laboratory of the Department of Psychology, The University of Melbourne, Australia.

Participants:

There were 5 male and 5 female healthy individuals in each experiment between the ages of 18–25 years (Experiment 1) and 38–55 years (Experiment 2).

Interventions:

Participants in Experiment 1 were aroused by auditory stimuli every (i) 2 min, (ii) 1 min, and (iii) 30 sec of sleep for 90 min after the first indication of sleep. In a control condition, participants slept undisturbed for one NREM sleep cycle. Experiment 2 compared the control with the 30-sec condition in the young adults and in an additional group of middle-aged adults.

Measurements and Results:

The dependent variables were blood pressure (BP) and heart rate (HR). In Experiment 1, sleep fragmentation at higher frequencies retarded the fall in BP over sleep onset but did not affect the underlying sleep levels. Experiment 2 showed that there were no age differences on the effect of arousals on changes in BP and HR during sleep.

Conclusions:

This paper supports the hypothesis that repetitive arousals from sleep independently contribute to elevations in BP at night.

Citation:

Carrington MJ; Trinder J. Blood pressure and heart rate during continuous experimental sleep fragmentation in healthy adults. SLEEP 2008;31(12):1701–1712.     

Heart Rate Perception and Heart Rate Control

Twenty-one subjects look the Autonomic Perception Questionnaire (APQ) and later were given another test of ability to perceive heart activity. The second test involved subjects' tracking of their own heart rates (HR). They were then tested for ability to increase and decrease HR from their resting baseline levels. No significant relationships were found between HR control and APQ score. HR decrease success seemed to depend mainly on respiration differences between rest and decrease periods. The subjects who achieved high scores on the heart tracking test increased HR significantly better than did low scorers. This heart perception vs HR increase relationship did not depend upon respiration rate, respiration amplitude, or baseline HR differences between high and low scorers on the tracking test. A low correlation between APQ and tracking score seemed to indicate that the two perception tests measured different attributes of the subjects.     

Prevalent Hypertension and Stroke in the Sleep Heart Health Study: Association with an ECG-derived Spectrographic Marker of Cardiopulmonary Coupling

Study Objectives:

The electrocardiogram (ECG)-based sleep spectrogram generates a map of cardiopulmonary coupling based on heart rate variability and respiration derived from QRS amplitude variations. A distinct spectrographic phenotype, designated as narrow-band elevated low frequency coupling (e-LFC_NB), has been associated with central apneas and periodic breathing and predicts sleep laboratory failure of continuous positive airway pressure therapy. This study assesses, at a population level, the associations of this spectrographic biomarker with prevalent cardiovascular disease using the Sleep Heart Health Study (SHHS)-I dataset.

Design:

Retrospective analysis of the Sleep Heart Health Study-I dataset.

Setting:

Laboratory for complex physiologic signals analysis.

Measurements and Results:

The fully-automated ECG-derived sleep spectrogram technique was applied to 5247 (of the original 6441) polysomnograms from the SHHS-I. Associations were estimated with use of various drugs and pathologies including prevalent hypertension and cardiovascular and cerebrovascular disease. Increasing with age and more common in males, e-LFC_NB is also associated with greater severity of sleep apnea and fragmented sleep. After adjustment for potential confounders, an independent association with prevalent hypertension and stroke was found.

Conclusions:

An ECG-derived spectrographic marker related to low frequency cardiopulmonary coupling is associated with greater sleep apnea severity. Whether this biomarker is solely a sign of more severe disease or whether it reflects primary alterations in sleep apnea pathophysiology (which may either cause or result from sleep apnea) is unknown. This ECG-based spectral marker is associated with a higher prevalence of hypertension and stroke.

Citation:

Thomas RJ; Weiss MD; Mietus JE; Peng CK; Goldberger AL; Gottlieb DJ. Prevalent hypertension and stroke in the sleep heart health study: association with an ECG-derived spectrographic marker of cardiopulmonary coupling. SLEEP 2009;32(7):897-904.     

利用R—R间期相关维数对心率变异的分析

本文应用混沌理论，研究了心率变异情况下Ｒ－Ｒ间期的相关维数。对正常生理状态下人清醒与睡眠阶段，及临床－２４小时ＨＯＬＴＥＲ记录的Ｒ－Ｒ间期，分段计算其相关维数，结果表明，当其中某段Ｒ－Ｒ间期发生明显改变时，相关维减小。     

运动心率检测系统的研制及心率与肌氧含量同步实验研究

研制了一种便携式运动心率实时无线检测系统,通过不断提取心脏跳动时两个相邻心电R波的时间间期来实现高强度运动训练中运动员心率的瞬时无线检测.与肌氧含量检测仪作了同步实验,初步研究了心脏负荷与心率及肌氧含量之间的关系.