Drowsiness Detection: Effects of Feedback Based on EEG

DESCRIPTION:( provided by applicant) Fatigue management is a critical public health concern in today's 24-hour society. Fatigue-related accidents and decreased productivity cost the U.S. over $77 billion each year. The ability to objectively and reliably rnonitor fatigue levels in real-time while individuals engage in nornnal daily activities would significantly improve safety, increase productivity and save lives. In Phase I, the effectiveness of providing real-time feedback based on EEG indices of drowsiness in decreasing the impact of fatigue induced by sleep deprivation will be investigated. Subjective and objective measures of drowsiness will be obtained while subjects perform vigilance, memory and driving simulator tasks. Verbal messages and warning alarms will be delivered when EEG indices of drowsiness are identified by the Company's B-Alert software which classifies each second of EEG on a continuum from alert to sleep onset. The duration and magnitude of the feedback effects on performance and the perceived impact on drowsiness will be quantified. Subject's ability to predict the onset of sleep will also be measured before and after feedback sessions to determine whether the system has utility as a training device. A reliable EEG-based drowsiness detection device will be completed once the criteria for feedback are established. PROPOSED COMMERCIAL APPLICATION: The Drowsiness Detection Device will be marketed to employers of airline pilots, truck/bus drivers, railroad operators and other shift workers in safety sensitive positions. The system also has utility as a training device to increase subjective awareness of drowsiness. Medical applications of the system include continuous monitoring of alertness in patients with sleep disorders, treatment outcome assessment and pharmaceutical evaluations of medications that induce daytime drowsiness.