Evaluating dynamic changes of driver's awakening level by grouped /spl alpha/ waves

Describes the system of automatically detecting grouped /spl alpha/ waves of EEGs using a convolution with special weighting factors such as moving average methods. A drop of human awakening level has a close relation to appearances of grouped /spl alpha/ waves. Then using this system, it is possibl...

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Bibliographic Details
Main Authors: Fukuda, C., Funada, M.F., Ninomija, S.P., Yazu, Y., Daimon, N., Suzuki, S., Ide, H.
Format: Conference Proceeding
Language:English
Subjects:
Cause effect analysis
Convolution
Educational institutions
Electroencephalography
Frequency
Humans
Low-frequency noise
Noise level
Pattern analysis
Sleep
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Summary:Describes the system of automatically detecting grouped /spl alpha/ waves of EEGs using a convolution with special weighting factors such as moving average methods. A drop of human awakening level has a close relation to appearances of grouped /spl alpha/ waves. Then using this system, it is possible to detect driver's low awakening condition and prevent traffic accidents caused by this condition. The system has two important points. The first, because actual data contain various kinds of noise, this system separates grouped /spl alpha/ waves from those. The second, the system detects this condition as soon as grouped /spl alpha/ waves appear. As the result of analyzing actual EEGs taken during driving a car, we find out the fact that intervals of grouped /spl alpha/ waves appearance fluctuate.
DOI:10.1109/IEMBS.1994.415451