Drowsy Detection using EEG and Image processing
Drowsiness detection has been studied in the context of evaluating products, assessing driver alertness, and managing ofﬁce environments. Drowsiness level can be readily detected through measurement of human brain activity. The electroencephalogram (EEG), a device whose application relies on adhering electrodes to the scalp, is the primary method used to monitor brain activity. The many electrodes and wires required to perform an EEG place considerable constraints on the movement of users, and the cost of the device limits its availability. For these reasons, conventional EEG devices are not used in practical studies and businesses. Many potential practical applications could beneﬁt from the development of a wire-free, low-priced device; however, it remains to be elucidated whether portable EEG devices can be used to estimate human drowsiness levels and applied within practical research settings and businesses. In this study, we outline the development of a drowsiness detection system that makes use of a low-priced, prefrontal single-channel EEG device and evaluate its performance in an ofﬂine analysis and a practical experiment.In this project we have used both eeg and camera combine together to assess drowsiness based on blink behavior.Our experimental results shows that our system is more secure and reliable.
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