A comprehensive review of heart rate variability as an indicator in the regulation of the autonomic nervous system by acupuncture:a bibliometric analysis

This study sought to conduct a bibliometric analysis of acupuncture studies focusing on heart rate variability(HRV)and to investigate the correlation between various acupoints and their effects on HRV by utilizing association rule mining and network analysis.A total of 536 publications on the topic of acupuncture studies based on HRV.The disease keyword analysis revealed that HRV-related acupuncture studies were mainly related to pain,inflammation,emotional disorders,gastrointestinal function,and hypertension.A separate analysis was conducted on acupuncture prescriptions,and Neiguan(PC6)and Zusanli(ST36)were the most frequently used acupoints.The core acupoints for HRV regulation were identified as PC6,ST36,Shenmen(HT7),Hegu(LI4),Sanyinjiao(SP6),Jianshi(PC5),Taichong(LR3),Quchi(LI11),Guanyuan(CV4),Baihui(GV20),and Taixi(KI3).Additionally,the research encompassed 46 reports on acupuncture animal experiments conducted on HRV,with ST36 being the most frequently utilized acupoint.The research presented in this study offers valuable insights into the global research trend and hotspots in acupuncture-based HRV studies,as well as identifying frequently used combinations of acupoints.The findings may be helpful for further research in this field and provide valuable information about the potential use of acupuncture for improving HRV in both humans and animals.

Physiological signal processing in heart rate variability measurement:A focus on spectral analysis

Human physiological(biological)systems function in such a way that their complexity requires mathematical analysis.The functioning of the brain,heart and other parts are so complex to be easily comprehended.Under conditions of rest or work,the temporal distances of successive heartbeats are subject to fluctuations,thereby forming the basis of Heart Rate Variability(HRV).In normal conditions,the human is persistently exposed to highly changing and dynamic situational demands.With these demands in mind,HRV can,therefore,be considered as the human organism’s ability to cope with and adapt to continuous situational requirements,both physiologically and emotionally.Fast Fourier Transform(FFT)is used in various physiological signal processing,such as heart rate variability.FFT allows a spectral analysis of HRV and is great help in HRV analysis and interpretation.

Drinking a Structured Water Product on Markers of Hydration,Airway Health and Heart Rate Variability in Thoroughbred Racehorses:a Small-scale,Clinical Field Trial

Racehorses in training are in situations of repeated stress that may have effects on hydration and health.It was hypothesized that daily consumption of a structured water(SW)product for 4 weeks will result in improved hydration,improved upper airway health and increased heart rate variability.Two groups of Thoroughbred racehorses matched for physiological,training and racing attributes were studied for 4 weeks.One group(n=17)received 10 L(about 15%)of their daily water as SW(followed by ad libitum filtered deep well water)and the control group(n=15)only filtered deep well water.Blood samples and bioelectrical impedance analysis(BIA)measures were obtained at baseline,2 and 4 weeks.Hydration was assessed using BIA.The upper airway was assessed by nasopharyngeal endoscopy at baseline and weekly within 60 minutes of breezing.On weekly breeze days heart rate was recorded at rest,during exercise and recovery and data were analysed for heart rate variability.Compared to controls,horses drinking SW showed increased hydration improved upper airway health post-breezing and increased heart rate variability.It is concluded that drinking 10 L daily of SW increased hydration and may have conferred some wellness benefits.

Effects of Different Types of Verbal Activities on Heart Rate Variability

In the present study, the effects of different types of verbal activities on heart rate variability (HRV) were investigated. ECG signals were recorded in ten volunteers during resting (R), reading silently (RS), reading aloud (RA) and talking freely (TF). Time domain, frequency domain and Poincaré plot measures of HRV were calculated for analyzing. Time domain parameter of pNN50, frequency domain parameter of LF (n.u.) and Poincaré plot parameter of SD1/SD2 were found statistically difference in RA and TF compared to R and RS. The results in this study show that HRV decreased while subjects were reading aloud and talking freely. The results also indicated that verbal activities of reading aloud and talking freely improve the sympathetic nervous activity.

Noisy ECG Signal Data Transformation to Augment Classification Accuracy

In this era of electronic health,healthcare data is very important because it contains information about human survival.In addition,the Internet of Things(IoT)revolution has redefined modern healthcare systems and management by providing continuous monitoring.In this case,the data related to the heart is more important and requires proper analysis.For the analysis of heart data,Electrocardiogram(ECG)is used.In this work,machine learning techniques,such as adaptive boosting(AdaBoost)is used for detecting normal sinus rhythm,atrial fibrillation(AF),and noise in ECG signals to improve the classification accuracy.The proposed model uses ECG signals as input and provides results in the form of the presence or absence of disease AF,and classifies other signals as normal,other,or noise.This article derives different features from the signal using Maximal Information Coefficient(MIC)and minimum Redundancy Maximum Relevance(mRMR)technique,and then classifies them based on their attributes.Since the ECG contains some kind of noise and irregular data streams so the purpose of this study is to remove artifacts from the ECG signal by deploying the method of Second-Order-Section(SOS)(filter)and correctly classify them.Several features were extracted to improve the detection of ECG data.Compared with existing methods,this work gives promising results and can help improve the classification accuracy of the ECG signals.

Cardiovascular age of aviation personnel: based on the principal component analysis of heart rate and blood pressure variability

Objective: To introduce a method to calculate cardiovascular age, a new, accurate and much simpler index for assessing cardiovascular autonomic regulatory function, based on statistical analysis of heart rate and blood pressure variability (HRV and BPV) and baroreflex sensitivity (BRS) data. Methods: Firstly, HRV and BPV of 89 healthy aviation personnel were analyzed by the conventional autoregressive (AR) spectral analysis and their spontaneous BRS was obtained by the sequence method. Secondly, principal component analysis was conducted over original and derived indices of HRV, BPV and BRS data and the relevant principal components, PCi orig and PCi deri (i=1, 2, 3,...) were obtained. Finally, the equation for calculating cardiovascular age was obtained by multiple regression with the chronological age being assigned as the dependent variable and the principal components significantly related to age as the regressors. Results: The first four principal components of original indices accounted for over 90% of total variance of the indices, so did the first three principal components of derived indices. So, these seven principal components could reflect the information of cardiovascular autonomic regulation which was embodied in the 17 indices of HRV, BPV and BRS exactly with a minimal loss of information. Of the seven principal components, PC2 orig , PC4 orig and PC2 deri were negatively correlated with the chronological age ( P <0 05), whereas the PC3 orig was positively correlated with the chronological age ( P <0 01). The cardiovascular age thus calculated from the regression equation was significantly correlated with the chronological age among the 89 aviation personnel ( r =0.73, P <0 01). Conclusion: The cardiovascular age calculated based on a multi variate analysis of HRV, BPV and BRS could be regarded as a comprehensive indicator reflecting the age dependency of autonomic regulation of cardiovascular system in healthy aviation personnel.

Holter ECG-Based Apnea Hypopnea Index to Screen Obstructive Sleep Apnea: A New Proposal and Evaluation of Feasibility

Obstructive sleep apnea syndrome (OSAS) is a common sleep disorder. It has been reported that approximately 40% of patients with moderate or severe OSAS die within the first eight years of disease. In hospitals, OSAS is inspected using polysomnography, which uses a number of sensors. Because of the cumbersome nature of this polysomnography, an initial OSAS screening is usually conducted. In recent years, OSAS screening techniques using Holter electrocardiogram (ECG) have been reported. However, the techniques so far reported cannot perform an OSAS severity assessment. The present study presents a new method to distinguish the obstructive sleep apnea (OSA) and non-OSA epochs at one-second intervals based on the Apnea Hypopnea Index assessment, defined as the duration of continuous apnea. In the proposed method, the time-frequency components of the heart rate variability and three ECG-derived respiration signals calculated by the complex Morlet wavelet transformation are adopted as features. A support vector machine is employed for classification. The proposed method is evaluated using three eight-hour ECG recordings containing OSA episodes from three subjects. As a result, the sensitivity and specificity of classification are found to reach approximately 90%, a level suitable for OSAS screening in clinical settings.

Comparison between Fast Fourier Transform and Autoregressive Model on Analysis of Autonomic Nervous Function after Food Intake in Women

Purpose: Heart rate variability (HRV) is acknowledged as a useful tool to estimate autonomic function. Fast Fourier transform (FFT) and autoregressive model (AR) are used for power spectral analysis of HRV. However, there is little evidence of agreement between FFT and AR in relation to HRV following food intake in females. In the present study, we applied both FFT and AR after food intake during the follicular and luteal phases, and compared raw low-frequency (LF) and high- frequency (HF) powers, and LF/HF ratio obtained with the two power-spectral analytical methods. Methods: All subjects participated in two sessions: follicular phase session and luteal phase session. In each session, R-R intervals were continuously recorded before and after meals, and power spectral analysis of heart rate variability was performed. We analyzed low-frequency power (LF: 0.04 - 0.15 Hz) and high-frequency power (HF: 0.15 - 0.40 Hz) by using FFT and AR. LF and HF power were computed for each 30 sec, 1 min, 2.5 min, and 5 min of the 5-min R-R data before meal intake and at 20, 40, 60 and 80 min after meal intake. The LF/HF ratio was calculated as an index of sympathovagal balance. Results: In the present study, after 30 sec and 1 min of segment analysis, there was little interchangeability between AR and FFT in LF, HF, and LF/HF ratio in both follicular and luteal phases. In 2.5 min or 5 min of segment analysis, there was interchangeability between FFT and AR in LF and HF, but not in the LF/HF ratio in both follicular and luteal phases. Additionally, FFT underestimated HRV compared with AR, and the extent of underestimation increased with increasing AR value. Conclusion: FFT underestimated HRV compared with AR, and FFT correlated poorly with AR when the analysis segment was shortened.

自然驾驶状态下城市地下环道驾驶人心理负荷研究

为探究城市地下环道驾驶人心理负荷特性,组织驾驶人自然驾驶试验,使用生理仪获取自然驾驶状态下驾驶人心电信号数据。以驾驶人心率、心率增长率和心率变异性指标为关键变量,基于因子分析法构建心理负荷量化模型,揭示地下环道平曲线半径、曲线类型、出入口以及熟练程度对驾驶人心理负荷的影响。研究表明:心率指标和心率变异性指标分别与地下环道平曲线半径呈负相关和正相关关系;驾驶人心理负荷与平曲线半径呈负相关,在相同半径条件下,连续曲线场景下的心理负荷显著高于单个曲线场景,且连续曲线间负荷累积作用超过单一曲线半径对驾驶人心理负荷的影响;入口段驾驶人心理负荷比出口段高21.39%;非熟练驾驶人心理负荷比熟练驾驶人高30.75%;建议在城市地下环道出入口和曲率变化区段增设视线诱导设施,设计车速为20~40 km·h^(-1)时,平曲线半径不宜小于30 m。

基于ECG指标的山区公路线形对驾驶员特性的影响研究

为获得山区道路纵坡路段线形对驾驶员特性的影响情况,利用数据采集(DAQ)卡和LabVIEW图形编程软件建立驾驶员心电(ECG)采集系统,结合生理学、医学心理学、工程心理学和人机工程学等方面理论方法和研究手段,建立驾驶员心率增长率与山路线形指标的回归模型。对驾驶员心率变异性(HRV)进行分析。结果表明:长大下坡路段坡度为3.5%左右时,驾驶员心率增长率超过40%,其心里最为紧张,而且HRV频域测量指标中的低频段功率值(LF)与高频段功率值(HF)之比(LF/HF)值在整个下坡过程中呈上升趋势,表明驾驶员交感神经活跃,易出现驾驶疲劳,对安全行车极为不利。

基于心率变异性的长航时模拟飞行疲劳评估

目的分析长航时模拟飞行中执行夜间飞行任务的驾驶员的状态,初步对受试者夜间执行任务的状态和可能预警点进行评估。方法选取8名健康男性,每2人一组分别执行机长和副机长的任务,共4组,开展模拟48 h连续飞行任务,其中,机长和副机长进行轮班制度,每飞行4 h进行45 min的睡眠以及45 min的恢复,根据该模拟飞行任务中所采集的心电数据,利用心率变异性(HRV)方法对试验对象的疲劳程度进行分析。结果HRV指标区分疲劳与非疲劳状态准确率大于90%的段落主要分布在夜间,且上半夜相较于下半夜飞行员的疲劳程度更大,试验第2日相较于第1日飞行员疲劳感更为明显。结论HRV分析体现了不同状态下的自主神经系统变化,通过结合相关分类模型,可靠地区分了模拟飞行试验中飞行员的疲劳与非疲劳状况。

心房颤动射频消融术后结合益气养阴法治疗的临床疗效观察

目的观察益气养阴法结合西医常规治疗对房颤射频消融术后康复的临床疗效。方法选取2020年1月—2022年1月在本院就诊的60例心房颤动并进行射频消融术的患者为研究对象,并按照随机数字表法分为对照组和治疗组,每组30例。其中,对照组术后服用利伐沙班进行治疗,治疗组在利伐沙班的基础上服用益气养阴中药汤剂进行中西医结合治疗,对比两组治疗效果。结果术前,两组SDNN值降低情况比较,组间差异无统计学意义(P>0.05);对照组治疗前后比较,差异有统计学意义(P<0.05);治疗组治疗前后比较,差异有统计学意义(P<0.001);治疗后组间比较,差异有统计学意义(P<0.001)。两组患者分别在术后3个月后进行动态心电图监测,观察临床疗效。治疗组总有效率高于对照组,组间差异有统计学意义(P<0.05)。结论房颤射频消融术后结合中医与西医的综合治疗手段,能够有效降低术后房颤的复发率,并在显著提高患者的临床疗效方面展现出显著优势。

基于心率变异性的飞行员脑力负荷特征

为了探索五边飞行不同阶段飞行员脑力负荷水平,寻找表征脑力负荷的心电指标,对飞行学员展开五边飞行任务的六自由度模拟飞行实验,测量飞行过程中的脑力负荷水平,采集不同飞行阶段飞行员心电各指标数据,利用因子分析构建飞行员脑力负荷模型,分析和验证不同飞行阶段飞行员脑力负荷的变化特征。结果表明:相比心率指标,心率变异性指标在测量飞行员脑力负荷时具有更高的信度和效度;起飞和上升阶段的脑力负荷处于较低水平并呈下降趋势;巡航阶段的脑力负荷水平较低且变化趋势平滑;进近着陆阶段的脑力负荷水平最高。此外,突发事件会显著影响脑力负荷,引起飞行员脑力负荷的显著增加。

Nonlinear Analysis of Physiological Time Series

The heart rate variability could be explained by a low-dimensional governing mechanism. There has been increasing interest in verifying and understanding the coupling between the respiration and the heart rate. In this paper we use the nonlinear detection method to detect the nonlinear deterministic component in the physiological time series by a single variable series and two variables series respectively, and use the conditional information entropy to analyze the correlation between the heart rate, the respiration and the blood oxygen concentration. The conclusions are that there is the nonlinear deterministic component in the heart rate data and respiration data, and the heart rate and the respiration are two variables originating from the same underlying dynamics.

基于单通道心电信号的家用睡眠分期方法

为了实现居家环境下的睡眠健康监测,提出基于可穿戴式单通道心电的不同睡眠阶段识别分析方法,研究了心电信号的27个心率变异性(HRV)特征分别在序列前向选择(SFS)、序列后向选择(SBS)和浮动序列前向选择(SFFS)3种不同方式下最优特征集的选取,设计了以堆栈式自编码器(SAE)建立的睡眠分期神经网络模型系统。结果表明:基于SFS-SAE的睡眠分期模型方法的分类效果最好,且相邻RR间期序列差值大于50 ms百分比(pNN50)、相邻RR间期序列差值的绝对中位差(MADRR)和庞加莱散点图中椭圆短轴(SD1)3种HRV特征都能在此模型系统中有效用于各睡眠阶段的识别,在清醒-睡眠(WAKE-SLEEP)分类、非快速眼动-快速眼动(NREM-REM)分类和浅睡-深睡(N1N2-N3)分类下的平均准确率分别为82%、80%和81%,基本满足家用睡眠分期判别,可用于睡眠疾病的日常筛查,是对多导睡眠图睡眠分析方法的有效补充。

基于积分均值模式分解和固有模态函数样本熵的阵发性房颤识别

针对阵发性房颤(PAF)发作持续时间较短难以捕捉,且现有识别算法抗噪性能较差易导致误检、漏检等问题,本研究提出一种基于积分均值模式分解(IMMD)和固有模态函数样本熵(IMFSE)的PAF识别方法。首先,对时长为20 min的心率变异性(HRV)信号片段进行IMMD分解得到一系列固有模态函数(IMF)分量,并计算IMFSE;然后,通过对IMFSE结果进行统计分析选取PAF识别的特征量;最后,利用支持向量机与交叉验证完成PAF识别。从PAF Prediction Challenge Database(AFPDB)数据库提供的正常受试者、PAF发作与远离PAF发作受试者心电信号中,分别获取25段时长为20 min的HRV信号片段,构成正常组、PAF发作组与PAF未发作组。通过对这75段HRV信号片段的实验发现:利用本方法进行PAF识别,识别准确率、敏感性、特异性分别可达到94%、96%、92%。所提出的PAF识别算法为进一步地快速准确自动检测PAF提供了参考,在可穿戴设备的长期自动检测识别PAF方面具有较大的应用前景。

Conscious Slower Breathing Predominates Parasympathetic Activity and Provides a Relaxing Effect, in Healthy Japanese Adult Women

Background: The optimal breathing pattern (BP) to effectively regulate autonomic nervous activity is yet to be determined. Objective: We aimed to clarify the effects of four BPs (BP-1, BP-2, BP-3, and BP-4) on autonomic nervous activity and mood changes. Methods: Eleven healthy adult female volunteers performed each BP in a sitting position for 5 min in a resting state. The time required for one breathing for BP-1 (30 breaths/min), BP-2 (20 breaths/min), BP-3 (15 breaths/min), and BP-4 (10 breaths/min) were 2 s, 3 s, 4 s, and 6 s, respectively. The inspiratory/expiratory time of one breathing was 1 s/1 s, 1 s/2 s, 2 s/2 s, and 2 s/4 s. The high-frequency component (HF) and low-frequency component (LF)/HF ratio during and before (control) performing a BP were calculated from heart rate variability data recorded using the wearable biometric information tracer M-BIT. Three mood changes, which are, “pleasure—unpleasure”, “relaxation—tension”, and “sleepiness—arousal”, in the subjects were assessed using the visual analog scale (VAS) before and after performing a BP. Results: Slower breathing induced an increase in HF power and a reduction in LF/HF ratio, indicating increased parasympathetic activity and decreased sympathetic dominance. Furthermore, VAS revealed that slower breathing increased the tendency to feel “pleasure”, “relaxation”, and “sleepiness”. Conclusion: Our results suggest that slower breathing predominates parasympathetic activity in the autonomic nervous system, resulting in a relaxing effect. This result may help lay the foundation for deriving breathing methods that efficiently regulate an individual’s autonomic activity.

ST段抬高型心肌梗死合并完全性右束支传导阻滞急诊PCI后心率变异性、QTcd和心电QRS电压影响的研究

目的探讨急性ST段抬高型心肌梗死(STEMI)合并完全性右束支传导阻滞行急诊经皮冠状动脉介入治疗(PCI)后,对患者心率变异性(HRV),QT校正离散度(QTcd)和心电QRS电压的影响。方法选择2019年12月至2021年12月梅州市人民医院诊断为STEMI并行急诊PCI或延期PCI患者150例,将急性STEMI合并完全性右束支传导阻滞行急诊PCI设定为观察组,急性STEMI合并完全性右束支传导阻滞行延期PCI设定为对照一组,急性STEMI无完全性右束支传导阻滞行急诊PCI设定为对照二组,每组各50例,评估其对HRV、QTcd和心电QRS电压的影响。结果治疗后,观察组QRS波群电压(aVF导联)及QTcd短于对照一组与对照二组,差异有统计学意义(P<0.05)。结论STEMI合并完全性右束支传导阻滞行PCI后,对HRV,QTcd和心电QRS电压的观测有助于临床筛选高危患者,利于远期预后。

痰湿壅盛型原发性高血压患者血栓前状态与心率变异性的相关分析

目的:探讨痰湿壅盛型原发性高血压患者血栓前状态(PTS)与心率变异性(HRV)的相关性。方法:收集广东省中医院符合纳入标准的痰湿壅盛型高血压患者159例,根据PTS各项结果分为观察组(79例)及对照组(80例)。对所有患者进行24 h动态心电图测量,比较两组患者一般情况、生化指标、PTS相关指标、HRV之间的差异,并采用Spearman相关性分析PTS各指标与HRV各指标之间的相关性。结果:两组患者性别、年龄、血压、合并糖尿病、合并冠心病、总胆固醇(TG)、高密度脂蛋白胆固醇(HDLC)、甘油三酯(TC)、低密度脂蛋白胆固醇(LDLC)比较,差异均无统计学意义(P>0.05)。观察组患者HRV各项指标均低于对照组,PTS各项指标均高于对照组,差异均有统计学意义(P<0.05)。Spearman相关分析结果显示:观察组凝血酶原时间(PT)、活化部分凝血活酶时间(APTT)与24 h每5分钟节段平均窦性R-R间期的标准差(SDANN)、24 h窦性R-R间期标准差(SDNN)、相邻正常R-R间期差值的均方根(rMSSD)、相邻正常R-R间期的差值大于50 ms的心搏占正常心搏总数的百分比(pNN50)呈明显正相关,纤维蛋白原(FIB)、D-二聚体(D-D)、血小板计数(PLT)与SDANN、SDNN、rMSSD、pNN50呈明显负相关。结论:与单纯原发性高血压患者相比,原发性高血压合并PTS患者自主神经功能受损更加明显。原发性高血压患者HRV相关指标与PTS有明显相关性,定期监测原发性高血压患者PTS及HRV相关指标,对其病情评估、改善预后具有重要意义。

动态心电图下脑梗死患者的心率变异性探究

目的 剖析脑梗死患者心率变异性分析在疾病防治方面的价值及效果。方法 选取本院2021年1-12月收治的44例脑梗死患者作为观察组研究对象,同期选择本院非脑梗死患者44例作为对照组研究对象。对所有研究对象均进行24h的动态心电图监测,分析其心率变异性,主要包括时域(SDNN、SDANN、SDNN Index、rMSSD、pNN50、TRIIDX)、频域(LF/HF、LF、HF)和散点图参数。对两组研究对象的心率变异性参数进行比较分析,同时分析脑梗死患者中午和深夜时段心率变异性参数。结果 观察组脑梗死患者的时域即SDNN、SDANN、SDNN Index、rMSSD、pNN50、TRIIDX等指标均低于对照组,差异明显(P<0.05);观察组脑梗死患者的频域即LF/HF、LF、HF等指标均高于对照组,差异明显(P<0.05);观察组散点图面积、长轴和短轴低于对照组(P<0.05);观察组患者中午散点图面积和长轴低,LF、HF参数低,心率水平高于深夜时段(P<0.05)。结论 脑梗死患者采取心率变异性分析,能基于时域、频域等参数变化,为疾病防治提供有益参考,值得临床加以重视和深入研究。