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使用单通道脑电图进行飞行中警觉状态的自动检测。

In-flight automatic detection of vigilance states using a single EEG channel.

作者信息

Sauvet F, Bougard C, Coroenne M, Lely L, Van Beers P, Elbaz M, Guillard M, Leger D, Chennaoui M

出版信息

IEEE Trans Biomed Eng. 2014 Dec;61(12):2840-7. doi: 10.1109/TBME.2014.2331189. Epub 2014 Jun 24.

Abstract

Sleepiness and fatigue can reach particularly high levels during long-haul overnight flights. Under these conditions, voluntary or even involuntary sleep periods may occur, increasing the risk of accidents. The aim of this study was to assess the performance of an in-flight automatic detection system of low-vigilance states using a single electroencephalogram channel. Fourteen healthy pilots voluntarily wore a miniaturized brain electrical activity recording device during long-haul flights ( 10 ±2.0 h, Atlantic 2 and Falcon 50 M, French naval aviation). No subject was disturbed by the equipment. Seven pilots experienced at least a period of voluntary ( 26.8 ±8.0 min, n = 4) or involuntary sleep (N1 sleep stage, 26.6 ±18.7 s, n = 7) during the flight. Automatic classification (wake/sleep) by the algorithm was made for 10-s epochs (O1-M2 or C3-M2 channel), based on comparison of means to detect changes in α, β, and θ relative power, or ratio [( α+θ)/β], or fuzzy logic fusion (α, β). Pertinence and prognostic of the algorithm were determined using epoch-by-epoch comparison with visual-scoring (two blinded readers, AASM rules). The best concordance between automatic detection and visual-scoring was observed within the O1-M2 channel, using the ratio [( α+θ )/β] ( 98.3 ±4.1% of good detection, K = 0.94 ±0.07, with a 0.04 ±0.04 false positive rate and a 0.87 ±0.10 true positive rate). Our results confirm the efficiency of a miniaturized single electroencephalographic channel recording device, associated with an automatic detection algorithm, in order to detect low-vigilance states during real flights.

摘要

在长途夜间飞行期间,困倦和疲劳程度可能会特别高。在这种情况下,可能会出现自愿甚至非自愿的睡眠时段,从而增加事故风险。本研究的目的是使用单一脑电图通道评估飞行中低警觉状态自动检测系统的性能。14名健康飞行员在长途飞行(10±2.0小时,驾驶大西洋2型和猎鹰50M型飞机,法国海军航空兵)期间自愿佩戴了小型化脑电活动记录设备。没有受试者受到该设备的干扰。7名飞行员在飞行过程中至少经历了一段自愿睡眠期(26.8±8.0分钟,n = 4)或非自愿睡眠期(N1睡眠阶段,26.6±18.7秒,n = 7)。基于检测α、β和θ相对功率变化的均值比较、比率[(α+θ)/β]或模糊逻辑融合(α、β),对10秒时段(O1-M2或C3-M2通道)进行算法自动分类(清醒/睡眠)。通过与视觉评分(两名盲法读者,采用美国睡眠医学学会规则)逐时段比较来确定算法的相关性和预后性。在O1-M2通道内,使用比率[(α+θ)/β]时,观察到自动检测与视觉评分之间的最佳一致性(良好检测率为98.3±4.1%,K = 0.94±0.07,假阳性率为0.04±0.04,真阳性率为0.87±0.10)。我们的结果证实了与自动检测算法相关联的小型化单通道脑电图记录设备在实际飞行中检测低警觉状态的有效性。

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