Date Approved


Graduate Degree Type


Degree Name

Engineering (M.S.E.)

Degree Program

School of Engineering


The goal of this thesis is to design and test a real-time Stage 1 sleep detection and warning system using a low-cost single dry-sensor EEG headset. Such a system would allow aircraft pilots or truck drivers to receive an auditory warning when they are beginning to fall asleep. The device designed in this study records a single EEG signal and filters it into low Alpha (7.5 - 9.25 Hz), high Alpha (10 - 11.75 Hz), low Beta (13 - 16.75 Hz), and high Beta (18 - 29.75 Hz) frequency bands. When the EEG transitions to match that of Stage 1 sleep for a short period of time, the device produces an audible alarm.

The system proved 81% effective at detecting sleep in a small sample group. All failures were due to false alarms. Compared to tradition sleep scoring, this device predicted and responded to the onset of drowsiness preceding stage 1 sleep.