Drowsy driving is a one of the most common cause of accident. The risk and danger that results due to drowsy driving are alarming. The drowsy driving usually happens when the driver has not slept enough, it can also happen due to continuous shift work, sleep disorders, medications, alcohols, illness. In this study, we have proposed development of a drowsiness detection system using a portable electroencephalograph (EEG) and a mobile device. This proposed mobile app is expected to minimize the accidents caused by drowsy driving [1]. By using Electroencephalogram (EEG) sensor, the condition of drowsiness is detected by recording the electrical activity that occurs in the human brain and is represented as a frequency signal. This frequency signal is transmitted to the mobile app using Bluetooth and will give an alarm notification when the drowsiness is detected. If the driver does not respond within a given time (e.g. greater than 1 minute) then it sends alert to the emergency contacts [1]. The brainwave from the EEG sensor is classified into four features, namely Delta, Theta, Alpha, and Beta waves.
Drowsiness, Electroencephalogram (EEG), Accident Prevention, Brain Wave, Mobile Application
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