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...     

Power Spectral Analysis of Heart Rate Variability of Driver Fatigue

IntroductionDrivingfatigue overloadinghas threatenedpeople s healthand life. Investigation datum from suggested that estimates ofthe contribution of driver mental fatigue to total trafficaccidents vary from 4% in 1980 to 25% in 1995[1]. Surveyresults revealed that 64% of respondents had experiencedfatigue on the road. In addition, 7% of the subject sampleclaimed to have had traffic accident due to fatigue.Drivingfatigue is a substantialproblem and serious threat inthe …     

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。     

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.     

外周化学感受器活动对心率变异性的影响

采用给健康、麻醉的豚鼠吸入纯氮气 (N2 )和纯氧气 (O2 )的方法 ,以兴奋或抑制外周化学感受器 ,观察外周化学感受器兴奋对心率变异性的影响 .吸入N2 引起TV、VLF、VLF/HF和LF/HF比值显著增加 ( p <0 0 5～ 0 0 0 1 ) .吸入纯氧后VLF和LF显著减少 ( p <0 0 5 ) .实验表明 :VLF随外周化学感受器的不同活动状态而改变 ,外周化学感受器兴奋对VLF的形成起了重要作用     

哈慈五行针对改善驾驶精神疲劳的实验

研究了基于中医磁疗理论的两组监视操作实验并分析其结果．A组实验从开始到结束共90min，中间无干扰，不间断；B组实验同为90min不间断，但在60—90min时段内，对实验样本的若干穴位进行加磁．实验结束后，对比两组实验测试指标的变化，这些指标主要包括判断正确率、闪频以及主观评价．结果表明，在特定穴位施加哈慈五行针可以改善驾驶员精神疲劳状态．     

Research progress in nonlinear analysis of heart electric activities

1INTRODUCTION THE WORLD IS NONLINEAR,AND THE HUMAN LIFE ACTIVITY IS ALSO NONLINEAR.FROM THE VIEWPOINT OF SYSTEM,HUMAN BEINGS(OR THE OTHER HIGHER ANIMAL)ARE THE MOST COM-PLEX SYSTEM IN THE NATURE.FOR SUCH A PHYSIOLOGICAL SYS-TEM WITH THE UTTERMOST COMPLEXI…     

Reducing the Effects of Driving Fatigue with Magnetic Stimulation

Introduction Drivingfatigueisaseriousproblemandbelievedtobea directorcontributingcauseofroad relatedaccidents.Fatigue isagradualandcumulativeprocessandisthoughttobe associatedwithadisinclinationforanyeffort,reduced efficiencyandalertnessandimpairedmentalperformance[1] Cognitiveeffortinvolvessustainedvigilance,selective attention,andcomplexdecisionmakingandoccasionally automatizedperceptual motorcontrolskills.Performanceover time,suchasthatrequiredduringdrivingusuallyrequire greatercognitivee…     

基于颈腰部肌电及脑电信号的疲劳驾驶检测

为了有效判别驾驶员的疲劳状态,结合生物力学分析提取了驾驶过程中的颈腰部肌电信号EMG和头部脑电信号EEG,并分析其特征参数在驾驶过程中的变化规律.结果表明:颈肌样本熵、颈肌复杂度、腰肌样本熵、腰肌复杂度、脑电样本熵、脑电复杂度这6个生理信号的特征参数值都随着驾驶时间的延长而逐渐降低,通过主成分分析可实现特征参数间的合理组合.基于多元回归理论,建立了能够有效预测疲劳驾驶的数学模型.状态验证结果表明,该模型对疲劳状态判别的正确率可达95%以上.     

基于EEG与EOG信号的疲劳驾驶状态综合分析

疲劳驾驶时,司机的脑电信号和眼电信号特征均发生显著变化,本文针对这两类信号进行分析研究,利用这两类数据综合分析判断司机是否处于疲劳驾驶状态.首先对采集的脑电信号进行小波包分解,提取信号中的α波,并计算其相对功率谱P;然后利用Pearson相关系数分析两路对称导联F7,F8中眨眼信号特征,去除干扰;最后利用BP神经元网络对眨眼信号进行识别,计算眨眼频率.结果表明,利用眼电信号和脑电信号特征综合分析司机眨眼动作,能准确识别出眨眼信号,并能正确检测人的驾驶疲劳状态的变化.