Effects of Impaired Glucose Metabolism on Heart Rate Variability and Blood Pessure Variability in Essential Hpertensive Patients

To investigate the effects of impaired glucose metabolism （IGM） on cardiovascular autonomic nervous systems in essential hypertensive （EH） patients by comparing heart rate variability （HRV） and blood pressure variability （BPV） in EH patients with or without type 2 diabetes mellitus （T2DM）. Simultaneous 24-h recordings of ambulatory ECG and blood pressure monitoring were performed in 36 male old patients with simple EH and 33 male old patients with EH combined with T2DM. HRV analysis included time domain parameters such as SDNN, SDANN, SDNNi, rMSSD and pNN50, and total spectral power （TP） of HRV, which mainly consists of VLF, LF and HF component along with LF/HF ratio, was also obtained. The value of ambulatory blood pressure was represented as the mean blood pressure （mean systolic/mSBP, diastolic/mDBP and pulse pressure/mPP） during different periods （24 h/24 h, day time/d and night time/n）. Standard deviation （SD） as well as coefficient of variance （CV） of blood pressure during each above-mentioned period were obtained to reflect the long-term BPV. Our result showed that SDNN, SDNNi, SDANN, rMSSD, PNN50, TP and HF of HRV in cases of EH with T2DM were all significantly lower than those in simple EH subjects （P〈0.05）. No significant differences in VLF or LF was found between the two groups （P〉0.05）, while LF/HF ratio was significantly higher in EH with T2DM patients than in simple EH subjects （P〈0.01）. Moreover, dmSBP, 24 h-mPP and dmPP were all significantly higher in EH with T2DM patients than in simple EH subjects （P〈0.05）, while nmSBP, 24 h-mSBP, 24 h-mDBP, dmDBP, nmDBP or nmPP showed no significant difference between this two groups of patients （P〉0.05）. And dSBPSD, dSBPCV and 24 h-SBPSD were all significantly higher in EH with T2DM patients than in simple EH subjects （P〈0.05）, while the other BPV indexes showed no significant difference between this two groups （P〉0.05）. It is concluded that the cardiovascular autonomic nervous systems in EH patients was further impaired by T2DM, displaying lowering of HRV and enlargement of BPV, which in turn induced abnormal structural and functional changes of cardiovascular systems. Therefore, improving cardiovascular autonomic nervous systems might reduce the occurrence of cardiovascular complications in the EH patients with IGM.

Analysis of heart rate variability based on singular value decomposition entropy

Assessing the dynamics of heart rate fluctuations can provide valuable information about heart status. In this study, regularity of heart rate variability （HRV） of heart failure patients and healthy persons using the concept of singular value decomposition entropy （SvdEn） is analyzed. SvdEn is calculated from the time series using normalized singular values. The advantage of this method is its simplicity and fast computation. It enables analysis of very short and non-stationary data sets. The results show that SvdEn of patients with congestive heart failure （CHF） shows a low value （SvdEn： 0.056±0.006, p 〈 0.01） which can be completely separated from healthy subjects. In addition, differences of SvdEn values between day and night are found for the healthy groups. SvdEn decreases with age. The lower the SvdEn values, the higher the risk of heart disease. Moreover, SvdEn is associated with the energy of heart rhythm. The results show that using SvdEn for discriminating HRV in different physiological states for clinical applications is feasible and simple.

Effects of Moxa (Artemisia Vulgaris) Smoke Inhalation on Heart Rate and Its Variability

Objective: To evaluate the changes of human heart rate (HR) and heart rate variability (HRV) during and after moxa smoke inhalation and to investigate the effects of moxa smoke on human autonomic nervous system. Methods: 24 healthy volunteers were exposed to moxa smoke with their HRV parameters measured before, during and after the moxa smoke inhalation. Results: The healthy volunteers exposed to moxa smoke had significant reductions in HR and also significant changes in HRV parameters. Conclusions: Moxa smoke can improve the autonomic nervous system activity. The inhalation of moxa smoke will induce a depressant effect on human body.

An Intelligent Household Heart Rate Meter

The measuring instrument which uses Sunplus SPCE061A MCU as the controller is a practical intelligent household heart rate meter.It can serve all people timely and effectively to detect the heart rate.It rings some voice alarm if the HRV is abnormal.Then it is decided whether to see a doctor at a convenient time for further diagnosis.The instrument has a feature of voice guidance that can save keyboard steps,which extends the scope of use.All people,old and young,the blind and the deaf,can use it by themselves.

Clinical Teleacupuncture between China and Austria Using Heart Rate Variability in Patients with Depression

In previous studies by the same research group it has been shown in post-stroke patients that the autonomic system can be affected by acupuncture. Within this study, teleacupuncture between China and Austria is used for quantifying the effects of heart rate variability (HRV) in Chinese patients suffering from depression. In 22 Chinese depression patients (17 f, 5 m;mean age ± SD 52.3 ± 10.6 years;range 31 - 70 years) electrocardiographic signals before, during and after acupuncture at the acupoint Jianshi (PC 5) were recorded in Harbin and analyzed in Graz using teleacupuncture via internet. HRV data were analyzed in the time and frequency domain and a protocol from Austria was sent to the team in China immediately after the treatment and recording session. Mean heart rate decreased significantly (p < 0.001) during and after acupuncture, whereas total HRV increased significantly during (p < 0.034) and after (p < 0.001) acupuncture, always immediately following manual needle stimulation. Furthermore, there is a marked decrease in balance between sympathetic and parasympathetic activity (low frequency/high frequency HRV ratio) during treatment. This study shows that HRV could be a useful parameter for quantifying clinical effects of acupuncture on the autonomic nervous system. Teleacupuncture between China and Austria over a distance of more than 8,500 km has been successfully used.

The Effect of Breathing Route on Heart Rate Variability—A within Subject Comparative Study

Background: The effect of traffic related emissions on Heart Rate Variability (HRV) has been previously demonstrated. However, the results of different studies on the relationship between ambient pollutants and specifically carbon monoxide (CO) on HRV are inconclusive and appear to reflect personal differences. The differences in methodology including breathing style and participants under study can possibly attribute to this variability. The aim of the present study is to assess the effect of the breathing route (Nasal/Oral) on the relationship between CO concentration and HRV. Methodology: Forty healthy participants (25 females, 15 males) between the ages of 15 - 50 years were included in the study. The participants strolled in a central bus station, staying for 10 minutes in three designated locations alternating nasal and oral breathing. CO concentration and HRV were continuously monitored. Frequency (LnLF, LnHF, LnLF/HF) and time domain (LnSDNN, LnRMSSD) HRV indices were computed. Analysis: MANCOVA, with HRV indices being the dependent variables and CO, gender and age being the independent variables was employed. Results: Significant interaction effects between breathing route and CO, and breathing route and gender on HRV (LnLF/HF) were found (p = 0.04 and 0.01 respectively). Both CO and age were found to affect LnSDNN and LnRMSSD. Conclusion: Breathing route emerges as a possible modifier of the relationship between air pollution and HRV and thus contributes to interpersonal differences obtained in studies investigating the effect of environmental pollution and HRV.

High frequency heart rate variability evoked by repetitive transcranial magnetic stimulation over the medial prefrontal cortex: A preliminary investigation on brain processing of acute stressor-evoked cardiovascular reactivity

Introduction: Transcranial Magnetic Stimulation (TMS) is a non-invasive technique for brain stimulation. Repetitive TMS (rTMS) over the medial Prefrontal Cortex (mPFC), Broadman Area 10 (BA10) may stimulate transynaptically perigenual Anterior Cingulate Cortex (pACC, BA 33), insula, amigdala, hypothalamus and connected branches of the Autonomic Nervous System (ANS) involved in stressorevoked cardiovascular reactivity. Stressors are associated with an increase in sympathetic cardiac control, a decrease in parasympathetic control, or both, and, consequently, an increase in systolic/stroke volume, total vascular impedance/resistance and heart rate, a decrease of baroreflex sensitivity, i.e., an increase in blood pressure/arterial tension. Objectives and Aims: The present work aims, using TMS and accordingly to Gianaros modeling, based on functional neuroimaging studies and previous neuroanatomical data from animal models, to probe the connectivity of brain systems involved in stressor-evoked cardiovascular reactivity and to explore TMS potential as a tool for detection and stratification of individual differences concerning this reactivity and hemorreological risk factors correlated with the development of Coronary Heart Disease (CHD). Methods: Both subjects, a 52 years old male and a 40 years old female with previous increased Low Frequency (LF)/High Frequency (HF) Heart Rate Variability (HRV) ratios (respectively, 4.209/3.028) without decompensated cardiorespiratory symptoms, gave informed consent, and ethico-legal issues have been observed. Electroencephalographic (EEG) monitoring has been performed for safety purposes. Immediately after administration, over the mPFC, of 15 pulses of rTMS, during 60 second, with an inductive electrical current, at the stimulating coil, of 85.9 Ampère per μsecond and 66 Ampère per μsecond, respectively, for male and female subjects (a “figure-of-eight” coil and magnetic stimulator MagLite, Dantec/Medtronic, have been used), HRV spectrum analysis (cStress software) has been performed (during 5 minutes, in supine position). Results: In both subjects, LF power, HF power and LF/HF ratio results, before and after rTMS administration, pointed towards sympathetic attenuation and parasympathetic augmentation (respectively, in male/female subject: decreased LF power—65.1 nu/69.3 nu, before rTMS;56.1 nu/41.6 nu, after rTMS;increased HF power—15.5 nu/22.9 nu, before rTMS;30.9 nu/45.5 nu, after rTMS). Conclusions: In this preliminary investigation, the existence of a link between “mind” and heart’s function has been put in evidence, through a reversible “virtual” lesion, of brain systems involved in cardiovascular control, caused by TMS. Repetitive TMS over mPFC decreased brain function involved in stressorevoked cardiovascular reactivity, suggesting the importance of TMS in the management of stress-related cardiovascular disorders.

基于调频连续波雷达的人体生命体征检测算法

针对现有雷达非接触生命体征检测精度低、实时性差等问题,提出一种基于调频连续波(FMCW)雷达的人体生命体征检测算法。首先,通过毫米波雷达获取生命体征信号;其次,利用改进的经验小波变换(EWT)算法,实现生命体征信号的自适应分解和重构,通过引入麻雀搜索算法(SSA)和模糊熵(FE)寻找频谱分割线的最优值;最后,通过改进频率插值的估计算法计算心率和呼吸频率。通过与医用重症监护仪进行对比实验验证所提算法的优越性和鲁棒性。实验结果表明,所提算法相较于小波变换(WT)算法、CEEMD(Complementary Ensemble Empirical Mode Decomposition)算法和VMD(Variational Mode Decomposition)算法,均方误差(MSE)分别减小了77.65、27.25和21.05,平均绝对百分比(MAPE)分别减小了7.33、4.33和3.42个百分点,实时性分别提高了0.72 s, 16.74 s和1.87 s。同时,利用所提算法也实现了对心率变异性(HRV)的检测。

睡眠剥夺对矿工风险感知的影响研究:基于生理试验

为探究睡眠剥夺对矿工风险感知的影响机理及作用效果,将72名矿工被试分为控制组和睡眠剥夺组,通过2种睡眠状况(正常、睡眠剥夺)×2种任务片段(基线段、逃生任务片段)的试验设计,分别记录分析不同任务片段下皮肤电活动(Electrodermal Activity,EDA)和心率变异性(Heart Rate Variability,HRV)的部分指标的变化特征。试验结果表明:逃生任务可以有效激活矿工的风险感知,在执行逃生任务时,矿工的C_(S)、L_(SC)和F_(L)/F_(H)显著上升,I_(BI)和P_(NN20)显著下降;睡眠剥夺会损害矿工的风险感知能力,研究发现,控制组被试逃生任务片段唤醒情绪和打破交感神经平衡的程度更大。研究结果可为睡眠剥夺相关的生理研究提供证据和参考,有助于提高煤矿的安全生产水平。

基于HRV的北方林区冰雪道路驾驶疲劳分析

为提高林区冰雪道路行车安全性,探讨林区冰雪道路驾驶员心理与生理疲劳状态,针对东北林区冰雪道路环境特殊性,通过实驾试验采集驾驶员的心电信号,基于心率变异性(HRV)指标的有效定量评价,结合指标间的灰色关联度分析,研究东北林区冰雪道路环境下驾驶员的心率(HR)、R-R间期标准偏差(SDNN)、低频与高频比值(LF/HF)及相关维数(D2)4个指标值间的变化规律及其随时间的变化规律。结果表明,驾驶员在林区冰雪道路驾驶过程中,HRV指标与HR关联次序为SDNN,D2,LF/HF,驾驶员在林区冰雪道路行车初期驾驶员紧张程度大;连续行车驾驶员精神负荷与体力负荷都会增大,出现疲劳累积效应。

肥胖合并重度阻塞性睡眠呼吸暂停低通气综合征患者的心率变异性分析

目的探讨肥胖合并重度阻塞性睡眠呼吸暂停低通气综合征(obstructive sleep apnea hypopnea syndrome,OSAHS)患者的心率变异性(heart rate variability,HRV)特征。方法回顾性分析2018年4月至2022年5月在西安交通大学第二附属医院行多导睡眠(polysomnography,PSG)监测确诊为重度OSAHS的78例患者,根据身体质量(body mass index,BMI)将患者分为肥胖并重度OSAHS组(n=43)和非肥胖并重度OSAHS组(n=35)。所有患者行PSG监测同时接受24 h动态心电图监测,进行HRV指标的组间差异分析及与临床指标的相关性分析。结果基础指标及PSG指标分析结果显示,与非肥胖并重度OSAHS组相比,肥胖并重度OSAHS组体质量、BMI、颈围、腰围、呼吸暂停低通气指数(apnea hypopnea index,AHI)显著升高。组间HRV分析结果显示,与非肥胖并重度OSAHS组相比,肥胖并重度OSAHS组的24 h正常R-R间期标准差(standard deviation of R-R interval,SDNN)、5 min R-R间期均值标准差(standard deviation of the averages of 5-minute R-R intervals,SDANN)、三角指数(triangle index,TI)、心率减速力(deceleration capacity of heart rate,DC)、清醒期SDNN及睡眠高频功率明显降低(P<0.05)。相关性结果显示肥胖并重度OSAHS患者中相邻R-R间期差值均方根(root mean square of the difference of adjacent R-R interval,rMSSD)与高血压病程呈负相关,TI、DC与AHI呈负相关。经校正颈围和腰围后的线性回归分析显示SDNN、SDANN、rMSSD与收缩压相关(P<0.05)。结论肥胖并重度OSAHS患者存在HRV指标下降,自主神经功能受到损害,心血管疾病的发生风险增加。

公路线形复杂程度对驾驶员HRV的影响研究

通过检测驾驶员心理、生理指标,观察公路线形复杂程度对驾驶员心率变异性(HRV)的影响,研究不合理公路线形对驾驶员行车安全的影响。对内蒙古境内6条公路的线形资料进行调查统计,利用赋值打分法确定各自的复杂程度;选取典型路段进行实驾试验,通过二列相关系数的计算及相应检验,得到心率变异分析的敏感指标;进而分析公路线形复杂程度对驾驶员心理、生理的影响。结果表明,HRV指标间期均值(MRR)、低高频比值(LF/HF)、样本熵(Samp En)对公路线形复杂程度响应敏感;即复杂程度过低会导致驾驶员由于驾驶任务简单出现反应迟缓、注意力难以集中等现象,影响行车安全;复杂程度过高会使驾驶员时刻保持精神高度集中状态,容易提前产生疲劳,从而威胁行车安全。

基于时变滤波经验模态分解的非接触式心率变异性估计方法

民航从业人员的身体健康状况是影响航空安全的重要因素,其中呼吸和心跳是极其重要的健康状况表征。为解决接触式或穿戴式测量系统对人员工作时的局限与影响,可采用线性调频连续波(Frequency-modulated continuous wave,FMCW)雷达达到非接触式测量的目的。由于生命体征信号具有时变、非平稳的特点,针对经验模态分解(Empirical mode decomposition,EMD)在信号分解中存在模态混叠现象的问题,使用时变滤波经验模态分解(Time varying filtering based on EMD,TVF-EMD)自适应信号的局部截止频率,可有效提高信号分离性能,解决模态混叠问题。利用TVF-EMD分解出的本征模态函数(Intrinsic mode functions,IMF)分量重构心跳对应的时域信号,估计心跳信号的频率和心跳节拍间隔(Inter-beat interval,IBI),进一步对心率变异性(Heart rate variability,HRV)相关指标进行估计。仿真实验与实测数据处理结果表明,TVF-EMD可从毫米波雷达测量信号中有效分离出呼吸与心跳信号。同时,从模态混叠程度及信号分离性能两方面对TVF-EMD与EMD方法分解效果进行了仿真分析,结果表明TVF-EMD能够有效解决模态混叠问题。因此,TVF-EMD方法能够准确有效地从毫米波雷达测量信号中提取生命体征信息,为IBI估计和HRV分析提供准确的时域信息,具有广阔的应用前景。

曲美他嗪对于陈旧性心肌梗塞病人心率变异性/HRV干预影响的随机交叉研究

目的:研究曲美他嗪（Trimetazidine）对于处于常规治疗中的心肌梗塞后病人的心率变异性（heart rate variability,HRV）的影响。方法:冠心病陈旧心 肌梗塞病人（OMI）,共59对;男性55对,女性4对。配对主要条件为:性别、 年龄、梗塞部位、梗塞后心功能、梗塞后时间、高血压病史及分级、糖尿病史。 采用病例配对、随机、交叉、单盲的试验设计。HRV参数为:全部正常窦性心 搏间期标准差（SDNN）;全程5min时间段NN均值标准差（SDANN）;全部相邻NN间期之差的均方根值（RMSSD）;三角指数:NN间期的总个数除以NN间期直方图的高度（横坐标时间单位为1/128秒）。结果分析:组间差别分析采用方差分析（ANOVA检验）;两组样本均数差别分析采用t’检验。结果:综合总的交叉试验结果（上述4个HRV分析参数）显示:曲美他嗪处理组心率变异性（HRV）改变不十分确切（PSDNN<0.05,PSDANN>0.05,P RMSSD>0.05、P三角指数>0.05）。但对于陈旧性心肌梗塞后左室射血分数/LVEF≤40％病人组与>40％组的心率变异性（HRV）差别的分析结果显示:曲美他嗪组心率变异性值增加具有明显差别（P<0.05）。对于陈旧性心肌梗塞合并Ⅱ型糖尿病病人组与非合并组的分析结果显示:曲美他嗪处理组心率变异性值增加具有显著意义（P<0.05）。结论:应用曲美?

基于Teager算子的短时HRV样本熵算法

在心率变异性(HRV)数据的短时非线性分析中,单纯的样本熵算法不能有效提取健康人和充血性心衰(CHF)患者的信号特征差异。为此,提出一种基于Teager能量算子的样本熵分析算法。采用Teager算子的预处理捕获心脏动力学活动中的异常节律变化,以强化样本熵分析效果。对MIT BIH数据库中样本的实验结果表明,该算法可反映健康人与CHF患者的短时HRV信号非线性复杂性的差异,为计算机分析诊断心衰等疾病提供新的辅助依据。

HRV的最大李雅普诺夫指数估计

对心率变异性(HRV)进行了研究,比较了心率正常者与心率失常者HRV之间的最大李雅普诺夫指数上的差别。人在正常状态和病理状态下的HRV信号最大李雅普诺夫指数是不同的,当出现病理心血管事件时,指数α减少,因此李雅普诺夫指数可作为人体是否异常或处于何种异常状态的特征刻画指标,本文心率正常者HRV信号的最大李雅普诺夫指数为0.45907,心率不齐者的最大李雅普诺夫指数是0.41472。它们均为混沌信号,但是处于心率不齐状态的节律混沌程度明显比处于心率正常状态的节律混沌程度低。

心悸寒证与热证心率变异性(HRV)与自主神经张力(交感和迷走)相关分析

[目的]观察心悸寒/热证心率变异性(heart rate variability,HRV)与自主神经张力(交感和迷走)相关性。[方法]使用前瞻性设计,平行对照方法,将141例住院及门诊患者按寒热证候归入实热、实寒、虚热、虚寒4组。观测HRV指标,时域指标SDNN、SDANN、RMSSD,频域指标TP、LF、HF、LF/HF。使用DMS动态分析软件,人工修正、去除伪差,自动分析24h连续心电信号(动态心电图)后,获得HRV各项指标。[结果]寒热辨证分组:热证82例(58.2%,82/141),其中实热32例,虚热50例;寒证59例(41.8%,59/141),均为虚寒证。SDNN、SDANN、RMSSD热证与寒证组间均无显著差异(P>0.05),虚寒组均大于虚热组(P<0.05)。TP、LF、HF热证与寒证组间均无显著差异(P>0.05),LF/HF热证组高于寒证(P<0.05);频域指标TP、HF、LF/HF虚热与虚寒均有显著差异(P<0.05),TP、HF虚寒大于虚热(P<0.05),LF/HF虚热组大于虚寒组(P<0.05),LF组间无显著差异(P>0.05),[结论]虚实与自主神经总张力相关,寒热与自主神经功能交感和迷走神经的张力平衡相关,热证与寒证自主神经总体能量无显著差异(P>0.05),热证组交感活动相对增强。

Machine learning noise exposure detection of rail transit drivers using heart rate variability

Previous studies have found that drivers’physiological conditions can deteriorate under noise conditions,which poses a potential hazard when driving.As a result,it is crucial to identify the status of drivers when exposed to different noises.However,such explo-rations are rarely discussed with short-term physiological indicators,especially for rail transit drivers.In this study,an experiment involving 42 railway transit drivers was conducted with a driving simulator to assess the impact of noise on drivers’physiological responses.Considering the individuals’heterogeneity,this study introduced drivers’noise annoyance to measure their self-noise-adaption.The variances of drivers’heart rate variability(HRV)along with different noise adaptions are explored when exposed to different noise conditions.Several machine learning approaches(support vector machine,K-nearest neighbour and random forest)were then used to classify their physiological status under different noise conditions according to the HRV and drivers’self-noise adaptions.Results indicate that the volume of traffic noise negatively affects drivers’performance in their routines.Drivers with different noise adaptions but exposed to a fixed noise were found with discrepant HRV,demonstrating that noise adaption is highly associated with drivers’physiological status under noises.It is also found that noise adaption inclusion could raise the accuracy of classifications.Overall,the random forests classifier performed the best in identifying the physiological status when exposed to noise conditions for drivers with different noise adaptions.

Exercise Fatigue Monitoring Based on R-Peak Detection Using UNET-TCN

Moderate exercise contributes to health, but excessive exercise may lead to physicalinjury or even endanger life. It is pressing for a device that can detect the intensity of exercise.Therefore, in order to enable real-time detection of exercise intensity and mitigate the risks of harmfrom excessive exercise, a exercise intensity monitoring system based on the heart rate variability(HRV) from electrocardiogram (ECG) signal and linear features from phonocardiogram (PCG)signal is proposed. The main contributions include: First, accurate analysis of HRV is crucial forsubsequent exercise intensity detection. To enhance HRV analysis, we propose an R-peak detectorbased on encoder-decoder and temporal convolutional network (TCN). Experimental resultsdemonstrate that the proposed R-peak detector achieves an F1 score exceeding 0.99 on real high-intensity exercise ECG datasets. Second, an exercise fatigue monitoring system based on multi-signal feature fusion is proposed. Initially, utilizing the proposed R-peak detector for HRV extractionin exercise intensity detection,which outperforms traditional algorithms, with the system achieving a classification performance of 0.933 sensitivity, 0.802 specificity, and 0.960 accuracy. To further improve the system, we combine HRV with the linear features of PCG. Our exercise intensitydetection system achieves 90.2% specificity, 96.7% recall, and 98.1% accuracy in five-fold cross-validation.

心率变异性与献血前心理评估的相关性研究

目的探讨献血者心率变异性(HRV)与献血前紧张程度之间是否存在关联。方法用心理焦虑自评量表(SAS)和紧张程度评估253名献血者献血前心理状态并分析其HRV时域和频域参数,分析SAS评分、紧张程度、HRV参数3者之间的相关性,比较不同类型献血者的差异性,并进行多元线性回归分析。结果247名献血者纳入分析,18~24岁献血者的HRV参数中有5项高于25岁以上献血者(P均<0.05),女性献血者焦虑程度(SAS评分41~46)高于男性(SAS评分35~43)(P<0.001);献血前SAS评分与紧张程度评估结果高度一致(r=0.970,P<0.001);献血前紧张程度、SAS评分均与HRV参数中的极低频(VLF)呈显著负相关(r=0.179,P=0.005),且关联独立于年龄、身体质量指数、性别等混杂因素(P<0.05)。结论HRV作为1种献血前心理评估工具,相对SAS和紧张程度评估,展现出更高的客观性,将HRV列入献血者常规筛查,可以评估献血前献血者焦虑程度,识别潜在的献血相关血管迷走神经反应(DRVR)风险人群,进而提升献血安全。