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机构地区:[1]煤炭总医院耳鼻喉科,北京100028 [2]首都医科大学附属北京中医院,北京100010 [3]北京交通大学土木建筑工程学院,北京100044
出 处:《交通信息与安全》2016年第3期96-100,107,共6页Journal of Transport Information and Safety
摘 要:患有阻塞性睡眠呼吸暂停低通气综合症(OSAHS)的驾驶员表现为日间嗜睡,驾驶中易发生错误操作,因而导致交通事故。为降低事故发生率,应识别OSAHS驾驶员发生事故前的驾驶状态。从驾驶员的生理角度,通过脑电波识别驾驶状态,提出交通事故前的预警指标。招募20名已被确诊患有OSAHS的驾驶员在模拟驾驶舱中进行模拟驾驶试验。被试者的驾驶环境、驾驶要求(如驾驶中不能接打电话、不能超速等)相同;在驾驶中采集OSAHS驾驶员的脑电波(α和β节律)变化、发生交通事故的时间和类型。通过宏观(波形图)及微观(数据)2个方面分析脑电波在不同驾驶状态下的变化。研究得出,交通事故发生时脑电波α节律受到抑制或消失;正常驾驶状态下和发生事故前的β/(α+β)均值具有显著差异性。以上2项均可作为驾驶嗜睡预警的指标。此外,提出事故发生前30s的β/(α+β)均值作为预警的临界阈值。The main symptom of drivers with obstructive sleep apnea hyperpnoea syndrome ( O SAH S) commonlyhave excessive daytime sleepiness, which would increase the probability of mis-operations that may result in accidents. Asa result, it is crucial to identify the physiological status of OSAHS drivers in order to avoid or reduce the probability ofaccidents. The brain waves, which can reflect the physiological changes of OSAHS drivers, are used to identify the drivingstate in this paper. The indicators for early warning of accidents are identified, 20 drivers with OSAHS are recruited todrive in a driving simulator while detecting their brain waves. The driving environment and requirements, such as prohibitionsof phone calls and over speed, etc., are identical for all of the drivers. The values of a and j3 rhythm of EEG as wellas accident types and occurrence times are recorded during the simulations. The fluctuations of brain waves under differentdriving conditions are analyzed from both macro (waveforms) and micro (data) perspectives. The results indicate that thea rhythm is either suppressed or vanished when an accident occurs. The mean value of β/(α+β) during an accident hassignificant distinctions with which in regular driving modes. As a result, both the change of a rhythm and the average value of β/(α+β) can be recognized as early warning indicators of sleepiness for OSAHS drivers during driving. Furthermore,the average value of β/(α+β) in 30 s before the accidents can be treated as a threshold value of early warning ofaccidents.
分 类 号:V351.3[航空宇航科学与技术—人机与环境工程]
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