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A Neuro-behavioral Test and Algorithms for Quantification of Sleepiness and Characterization of Wake-Sleep Transitions

机译:量化嗜睡和苏醒-睡眠转变特征的神经行为测试和算法

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A neuro-behavioral test has been developed that quantifies sleepiness by means of a convenient and relatively short-duration (15 minute) protocol, and using a class of algorithms that track wake to sleep transitions. Utilizing an ambulatory EEG monitoring combined with an auditory-based vigilance test, this method acquires both behavioral response (i.e., reaction time) and EEG waveforms that are simultaneously analyzed to produce a time-varying EEG-based drowsiness-sleepiness index (DSI). DSI index is computed from the time-varying power spectrum of EEG using an algorithm whose coefficients were determined based on an optimization procedure that maximized the correlation between the time profiles of DSI and those of the behavioral response. Sleepiness is quantified using an algorithm based on the consistency of the neuro-behavioral indices over the test period as well as the degree and profile of their degradation when the subject is incapable of maintaining alertness. This test was administered to 5 volunteers (separate from the subjects whose data were used for the above optimization of DSI) under the conditions of adequate prior night sleep and sleep restriction. Cross correlation analysis showed a close agreement between the time profiles of EEG-based DSI and behavioral response indices. Statistical analysis showed significant difference between the alert and sleepy conditions for the whole group as well as in each individual subject
机译:已经开发了一种神经行为测试,它通过方便且相对较短的时间(15分钟)协议并使用跟踪唤醒到睡眠过渡的一类算法来量化嗜睡。通过将动态脑电图监测与基于听觉的警惕性测试相结合,此方法可获取行为响应(即反应时间)和EEG波形,并同时对其进行分析以生成基于时变的EEG的嗜睡-嗜睡指数(DSI)。 DSI指数是使用一种算法根据脑电图的时变功率谱计算的,该算法的系数是根据优化程序确定的,该优化程序将DSI的时间曲线与行为响应的时间曲线之间的相关性最大化。在受试者无法保持警觉的情况下,使用一种算法根据在整个测试期间的神经行为指标的一致性以及它们的退化程度和程度,使用一种算法对困倦进行量化。在充足的先前夜间睡眠和睡眠限制条件下,对5名志愿者(与数据用于上述DSI优化的受试者分开)进行了该测试。互相关分析显示,基于EEG的DSI的时间曲线与行为反应指数之间存在密切的一致性。统计分析表明,整个组以及每个个体的警觉和困倦状况之间存在显着差异

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