Effect of 450 MHz Microwave Modulated with 217 Hz on Human EEG in Rest

Summary This study focuses on discrimination of changes, produced by low-level microwave exposure in intensity and time variability of the human EEG at rest. The power spectral density (PSD) method and nonlinear scaling analysis of the length distribution of low variability periods (LDLVP) were selected for analysis of the EEG signal. During the study, 19 healthy volunteers were exposed to a microwave (450 MHz) of 217 Hz frequency on-off modulation. The field power density at the scalp was 0.16 mW/cm². The experimental protocol consisted of ten cycles of repetitive microwave exposure. Signals from frontal, temporal, parietal and occipital EEG channels on EEG theta, alpha and beta rhythms were analysed. Exposure to microwave causes average increase of EEG activity. LDLVP analysis discriminated significant effect in time variability for 2 subjects (11%). PSD method detected significant changes in intensity for 4 subjects (21%). The effect of low-level microwave exposure is stronger on EEG beta rhythm in temporal and parietal regions of the human brain.     

基于EEG频谱特征的驾驶员疲劳监测研究

研究表明疲劳驾驶是引发交通伤亡事故的重要原因之一,因此有必要采取相应的预防措施。脑电是公认的睡眠(疲劳)金指标,因此论文提出了基于脑电频谱特征的驾驶员疲劳预测方法。采用了驾驶模拟实验中记录的三路驾驶员脑电信号,并利用驾驶员自评与专家评定两种方式相结合的方法将驾驶数据分为疲劳和清醒。针对脑电中眼电噪声很强的特点,对记录的脑电进行了自适应滤波消噪处理,结果显示可有效滤除眼电伪迹;然后根据脑电的频域特征比较突出且与疲劳相关的特点,从去噪后的脑电中提取出了的75个频谱特征;最后利用这些频谱特征,采用朴素贝叶斯分类的方法建立了驾驶员疲劳监测模型。实验结果表明,该方法能监测出驾驶员84%的疲劳状态。     

The Effects of the Level of Alertness During the Rest Period on Subsequent Performance

The aim of this study was to examine how to take an effective rest to prevent a decline in alertness at work. The relationship between alertness during the rest period and subsequent task performance were investigated. The electroencephalogram (EEG) during the rest period was classified into 3 types, and these types had a significant effect on performance after the rest period. Type 1 (increasing in theta, alpha 2, and beta 1 power) was the best one for carrying out the task, whereas performance gradually declined in Type 3 (no change in EEG activity). In the case of Type 1, the method that would relieve sleep inertia had a more positive impact on performance after the rest period.     

基于EEG的有限空间检修工脑疲劳特性研究

为了探究有限空间内检修工在高温高湿状态下的脑疲劳特征，采用对照与模拟有限空间作业环境相结合的方法，对作业人员脑电波变化进行监测，利用傅里叶变换对原波信号进行时频转换，提取相对频率、重心频率等特征参数。研究结果表明:在高温高湿的有限空间环境中，人体脑波功率变化幅度明显变大；在进入疲劳状态时有限空间环境的脑波功率低于对照组；高频的β波在高温高湿环境中减少的比例较大，平均下降7.1%；脑波重心频率由8 Hz降为6 Hz，平均下降11.3%，由α波变为θ波，大脑活动进入疲劳状态。说明有限空间的高温高湿环境对人体脑疲劳具有明显影响，可用于脑电智能穿戴监测设备监测工人脑疲劳状况。     

Individual changes in human EEG caused by 450 MHz microwave modulated at 40 and 70 Hz

This study was aimed to investigate the changes in the human electroencephalographic (EEG) signal caused by modulated low-level microwaves. The 450 MHz microwave exposure modulated at 40 Hz and 70 Hz frequencies was applied to a group of 15 volunteers. The field power density at the scalp was 0.16 mW/cm². Ten cycles of the exposure (1 min on and 1 min off) at both modulation frequencies were applied. Analysis of the EEG signal was performed using three different methods: nonlinear method of scaling analysis for length distribution of low variability periods (LDLVP), relative changes in EEG energy (S-parameter) and beta ratio (H-parameter). The analysis revealed significant changes caused by microwave for the whole group (H-parameter method). The exposure caused increase of the EEG beta power (S-parameter method). Statistically significant changes in EEG were detected for four subjects (26.7%) at 40 Hz modulation frequency (LDLVP method).     

Exploring differences between self-report and electrophysiological indices of drowsy driving: A usability examination of a personal brain-computer interface device

IntroductionImpaired driving has resulted in numerous accidents, fatalities, and costly damage. One particularly concerning type of impairment is driver drowsiness. Despite advancements, modern vehicle safety systems remain ineffective at keeping drowsy drivers alert and aware of their state, even temporarily. Until recently the use of user-centric brain-computer interface (BCI) devices to capture electrophysiological data relating to driver drowsiness has been limited. Method: In this study, 25 participants drove on a simulated roadway under drowsy conditions. Results: Neither subjective nor electrophysiological measures differed between individuals who showed overt signs of drowsiness (prolonged eye closure) during the drive. However, the directionality and effect size estimates provided by the BCI device suggested the practicality and feasibility of its future implementation in vehicle safety systems. Practical applications: This research highlights opportunities for future BCI device research for use to assess the state of drowsy drivers in a real-world context.     

工业噪声对脑认知影响的功率谱估计分析

为明确工业噪声对大脑认知的负面影响,采集火电厂球磨机的工业噪声,征集10名在校大学生在90 dB(A)的稳态工业噪声状态下及安静状态下的32导联脑电图(EEG)。采用傅里叶变换方法进行频域分析,提取δ频段、θ频段、α1频段、α2频段和β频段功率谱,并进行统计分析。结果表明:噪声环境与静音环境相比较,被试在δ频段、θ频段功率谱值明显增加,在α1频段内,噪声状态的功率谱值高于静音状态,在α2频段内正好相反。生产性噪声刺激可导致被试注意力分散,可通过各波段功率谱值或比率参数等评估噪声对认知的影响程度大小。     

Detecting fatigue in car drivers and aircraft pilots by using non-invasive measures: The value of differentiation of sleepiness and mental fatigue

Introduction: Fatigue is one of the most crucial factors that contribute to a decrease of the operating performance of aircraft pilots and car drivers and, as such, plays a dangerous role in transport safety. To reduce fatigue-related tragedies and to increase the quality of a healthy life, many studies have focused on exploring effective methods and psychophysiological indicators for detecting and monitoring fatigue. However, those fatigue indicators rose many discrepancies among simulator and field studies, due to the vague conceptualism of fatigue, per se, which hinders the development of fatigue monitoring devices. Method: This paper aims to give psychological insight of the existing non-invasive measures for driver and pilot fatigue by differentiating sleepiness and mental fatigue. Such a study helps to improve research results for a wide range of researchers whose interests lie in the development of in-vehicle fatigue detection devices. First, the nature of fatigue for drivers/pilots is elucidated regarding fatigue types and fatigue responses, which reshapes our understanding of the fatigue issue in the transport industry. Secondly, the widely used objective neurophysiological methods, including electroencephalography (EEG), electrooculography (EOG), and electrocardiography (ECG), physical movement-based methods, vehicle-based methods, fitness-for-duty test as well as subjective methods (self-rating scales) are introduced. On the one hand, considering the difference between mental fatigue and sleepiness effects, the links between the objective and subjective indicators and fatigue are thoroughly investigated and reviewed. On the other hand, to better determine fatigue occurrence, a new combination of measures is recommended, as a single measure is not sufficient to yield a convincing benchmark of fatigue. Finally, since video-based techniques of measuring eye metrics offer a promising and practical method for monitoring operator fatigue, the relationship between fatigue and these eye metrics, that include blink-based, pupil-based, and saccade-based features, are also discussed. To realize a pragmatic fatigue detector for operators in the future, this paper concludes with a discussion on the future directions in terms of methodology of conducting operator fatigue research and fatigue analysis by using eye-related parameters.     

Effect of modulated at different low frequencies microwave radiation on human EEG

This study is aimed to clarify whether effect of low-level microwave radiation on human brain differs at different modulation frequencies. Resting EEG recordings were done on different groups of healthy volunteers. The 450 MHz microwave radiation modulated at 40 and 70 Hz (15 subjects) and 217 and 1,000 Hz (19 subjects) frequencies was applied. The results of our previous study at 7, 14 and 21 Hz modulation were included into analysis. Ten cycles of the exposure (1 min off and 1 min on) at each fixed modulation frequencies were applied. The field power density at the scalp was always 0.16 mW/cm². Our results showed that microwave exposure increased the EEG energy at EEG frequencies lower or close to the modulation frequency. No effect was detected at EEG frequencies higher than the modulation frequency. Statistically significant changes were caused by exposure in the EEG alpha and beta frequency bands; no significant effect was detected in the theta band. Our results suggest that telecommunication devices with complex spectrum of modulation frequencies like mobile phone can affect all human EEG frequency bands.     

Non-Thermal Effect of Microwave Radiation on Human Brain

Summary This study focuses on an origin of interaction mechanism of microwave radiation with nervous system—quasi-thermal field effect. The microwave field can cause fluctuations and vibration of the charged particles and membranes in tissues. The hypothesis is, that this phenomenon is similar to the effect caused by Brown motion initiated by temperature and results in the same effects without rise in temperature. The electric field of 1 V/cm can introduce disturbance of the thermal equilibrium inside a cell of 10 μm radius, which is equivalent to disturbance produced by temperature rise of 1 K. The hypothesis, that microwave heating should cause an effect independent of the microwave modulation frequency, while field effect depends on modulation frequency, was examined experimentally. The 450 MHz microwave radiation, modulated at 7, 14 and 21 Hz frequencies, power density at the skin 0.16 mW/cm², was applied. The experimental protocol consisted of two series of five cycles of the repetitive microwave exposure at fixed modulation frequencies. Relative changes in EEG theta, alpha and beta rhythms of the group of 13 healthy volunteers were analysed. Analysis of the experimental data shows that: (1) statistically significant changes in EEG rhythms depend on modulation frequency of the microwave field; (2) microwave stimulation causes an increase of the EEG energy level; (3) the effect is most intense at beta1 rhythm and higher modulation frequencies. These findings confirm the quasi-thermal origin of the effect, different from average heating.