The Variation Regularity And Auto Stage Of Alertness Under Sleep Deprivation

With the acceleration of pace of life and the intensification of social competition, people whowork in specific industry have too much work pressure to sleep well, which leads to induction ofarousal level, executive capacity，attention，work efficiency，emergency response capacity,judgment of danger signal and increase of accident rate. Therefore, it is important to detect alertlevel in time and actively adjust tasks and workload. For example, astronauts usually work inspace for a long time. So, disorders in astronauts’ circadian rhythm caused by special changes inday and night of space and the loss sense of time cause by weightless environment of space alsoand the excessive pressure caused by overload work intensity will lead to astronauts’ sleepdeficiency and serious insomnia. Thus, it is important to actively adjust task intensity to ensuresuccessful completion by estimating astronauts’ alertness level.In this paper, on the basis of previous studies, first, we designed a36hour sleep deprivationexperiment. Second, we collected and analyzed spontaneous EEG, evoked potential, subjectivescale, and keystroke response. And we marked signals with artificial staging by sleep experts,subjective scale and length of sleep deprivation time of. Third, we perform the comprehensiveanalysis of spontaneous EEG in temporal, frequency, spatial domains and the nonlinear features,combine with analysis of P300, MMN, features of evoked potential land the behavior featureswe explore the variation regularity as the increase time of sleep deprivation and the physiologicalsignificance of the features. Last, multiplicate classification algorithms were used to realize theauto stage of alertness. And multi-modes character optimizations were used to achieve dimensionreduction and improve the speed of classification.The conclusions we get are as follows: if there has no working load, the alertness statusremains unchanged in the first12hours of sleep deprivation; among12to24hours of sleepdeprivation, the mental resource is not enough, which leads to alertness level dramaticallydeclined., and occipital area changed more apparently; among24to36hours of sleep deprivation,mental resource and biological clock effect offset, and alertness status maintains in secondplatform stability; BP algorithm is susceptible to optimal solution and its correct rate is95.67%, Incontrast, SVM algorithm has better effect with correct rate99.17%; FDR could reduce thedimension of features with high accuracy rate. PCA could reduce the dimension of features, butthe correct rate is lower.