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- W2913774951 abstract "In this study, we developed a hybrid brain--computer interface for drowsiness detection using electroencephalography (EEG) and electrooculography (EOG). Measurement was done with a single-channel EEG amplifier. A simple responsive task performed in a drowsy environment was used to experimentally demonstrate the advantages of the proposed system. Additionally, we performed the first investigation of hybrid EEG/EOG indices for drowsiness detection. Pearson's correlation analysis revealed that hybrid EEG/EOG indices were better correlated with the Karolinska Sleepiness Scale---the standard subjective measure---than were conventional EEG or EOG indices. Our investigation could contribute to both sleep research and the development of realtime drowsiness detection in the near future." @default.
- W2913774951 created "2019-02-21" @default.
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- W2913774951 date "2016-07-25" @default.
- W2913774951 modified "2023-09-23" @default.
- W2913774951 title "Feasibility Study of Drowsiness Detection Using Hybrid Brain-Computer Interface" @default.
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