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Quantification of sleepiness through principal component analysis of the electroencephalographic spectrum

机译:通过脑电图谱的主成分分析量化嗜睡

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Although circadian and sleep research has made extraordinary progress in the recent years, one remaining challenge is the objective quantification of sleepiness in individuals suffering from sleep deprivation, sleep restriction, and excessive somnolence. The major goal of the present study was to apply principal component analysis to the wake electroencephalographic (EEG) spectrum in order to establish an objective measure of sleepiness. The present analysis was led by the hypothesis that in sleep-deprived individuals, the time course of self-rated sleepiness correlates with the time course score on the 2nd principal component of the EEG spectrum. The resting EEG of 15 young subjects was recorded at 2-h intervals for 3250h. Principal component analysis was performed on the sets of 16 single-Hz log-transformed EEG powers (116Hz frequency range). The time course of self-perceived sleepiness correlated strongly with the time course of the 2nd principal component score, irrespective of derivation (frontal or occipital) and of analyzed section of the 7-min EEG record (2-min section with eyes open or any of the five 1-min sections with eyes closed). This result indicates the possibility of deriving an objective index of physiological sleepiness by applying principal component analysis to the wake EEG spectrum. (Author correspondence: putilov@ngs.ru)
机译:尽管近几年的昼夜节律和睡眠研究取得了长足的进步,但仍然存在的挑战是客观量化睡眠剥夺,睡眠受限和过度嗜睡的人的嗜睡情况。本研究的主要目的是将主成分分析应用于唤醒脑电图(EEG)频谱,以建立客观的嗜睡量度。本分析基于以下假设:在睡眠不足的个体中,自我评估的嗜睡的时程与EEG频谱第二个主要成分的时程得分相关。每隔2小时记录一次15名年轻受试者的静息EEG,持续3250h。对16个单Hz对数变换的EEG电源(116Hz频率范围)进行了主成分分析。自我感觉到的嗜睡的时间进程与第二主成分评分的时间进程密切相关,而与派生(额叶或枕骨)以及7分钟EEG记录的分析部分(2分钟睁着眼睛或任何眼睛的部分)无关闭眼的五个1分钟部分)。该结果表明,通过将主要成分分析应用于唤醒脑电图谱,可以得出生理性嗜睡的客观指标。 (作者通讯:putilov@ngs.ru)

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