Proceedings of the SPIE Defense and Security Symposium, Biomonitoring for Physiological and Cognitive Performance during Military Operations. John A. Caldwell, Nancy Jo Wesensten, Eds. Vol. 5797: pgs. 78-89. 2005. EEG quantification of alertness: Methods for early identification of individuals most susceptible to sleep deprivation Chris Berka 1* , Daniel J. Levendowski 1 , Philip Westbrook 1 , Gene Davis 1 , Michelle N. Lumicao 1 , Richard E. Olmstead 2 , Miodrag Popovic 3 , Vladimir T. Zivkovic 1 , Caitlin K. Ramsey 1 1 Advanced Brain Monitoring, Inc., 2850 Pio Pico Drive, Suite A, Carlsbad, CA USA 92008 2 VA Greater Los Angeles Healthcare System, 11301 Wilshire Blvd., Los Angeles, CA USA 90073 3 University of Belgrade, Faculty of Electrical Engineering, Serbia and Montenegro ABSTRACT Electroencephalographic (EEG) and neurocognitive measures were simultaneously acquired to quantify alertness from 24 participants during 44-hours of sleep deprivation. Performance on a three-choice vigilance task (3C-VT), paired- associate learning/memory task (PAL) and modified Maintenance of Wakefulness Test (MWT), and sleep technician- observed drowsiness (eye-closures, head-nods, EEG slowing) were quantified. The B-Alert ® system automatically classifies each second of EEG on an alertness/drowsiness continuum. B-Alert classifications were significantly correlated with technician-observations, visually scored EEG and performance measures. B-Alert classifications during 3C-VT, and technician observations and performance during the 3C-VT and PAL evidenced progressively increasing drowsiness as a result of sleep deprivation with a stabilizing effect observed at the batteries occurring between 0600 and 1100 suggesting a possible circadian effect similar to those reported in previous sleep deprivation studies. Participants were given an opportunity to take a 40-minute nap approximately 24-hours into the sleep deprivation portion of the study (i.e., 7 PM on Saturday). The nap was followed by a transient period of increased alertness. Approximately 8 hours after the nap, behavioral and physiological measures of drowsiness returned to levels prior to the nap. Cluster analysis was used to stratify individuals into three groups based on their level of impairment as a result of sleep deprivation. The combination of B-Alert and neuro-behavioral measures may identify individuals whose performance is most susceptible to sleep deprivation. These objective measures could be applied in an operational setting to provide a “biobehavioral assay” to determine vulnerability to sleep deprivation. Keywords: Sleep deprivation, individual differences, EEG, alertness, drowsiness, fatigue, vigilance performance, real- time monitoring, sleep debt. 1. INTRODUCTION Successful military operations require rapid and accurate decision-making and sustained vigilance often in challenging environments. Vigilance, short-term memory and decision-making are severely impacted by sleep deprivation with potentially dangerous consequences. The management of fatigue is increasingly considered a serious public health and safety concern 1-6 , since impaired vigilance is now believed to be a primary contributor to transportation and industrial accidents 7-12 . Recent NASA technical reports reveal that pilots often evidence brief episodes of unintentional sleep while flying 13-16 . The technical complexity and 24-hour schedule of the contemporary workplace demands the ability to sustain high levels of performance for extended periods of time 17 . As automation replaces manual labor, maintaining vigilance becomes more difficult with performance decrements increasing with time-on-task 18,19 . The adverse effects of sleep loss are calculated by quantifying the cumulative hours of sleep debt and accounting for interactions with circadian cycles 20,21 . The effects of even small amounts of sleep loss each night accumulate over time resulting in a “sleep debt”; as sleep debt increases, alertness, memory and decision-making are increasingly impaired 20- 24 . Individuals have been shown to become accustomed to this chronic accumulation of fatigue and are often unaware of the impact on their performance. Recent studies have suggested individuals may differ in their vulnerability to sleep deprivation 25-32 . These studies suggest that a fatigue management model that takes into account individual differences in susceptibility to sleep loss may be required to provide a safe, efficient, and highly productive workplace. * chris@b-alert.com; phone 1 760 720 0099; fax 1 760 720 0094; b-alert.com Do not copy or distribute 1