本研究是為了開發基於前額腦電訊號睏睡偵測系統所做的研究，而在這個電極點位置對日常生活的影響比較小。首先我們會觀察受試者從清醒到睏睡、從睏睡到睡著在行為和生理訊號上的變化，從觀察中可以發現在狀態轉換時，行為和生理訊號會有哪些變化。接著在這些變化中從Forehead-EEG擷取明顯且大部分受試者都會出現的現象作為特徵。然而，在觀察這些訊號前必須先確認該訊號的使用性（applicability）和可用性（feasibility）。
在使用性的部分會先觀察影片和訊號，確認在每個階段，也就是清醒到睏睡和睏睡到閉眼後，前額腦電訊號都可以觀察到受試者的現象；在可用性的部分則是針對閉眼前會出現的眼動訊號和閉眼後到睡眠各個階段的特徵，分別計算他們與影片觀察和腦電訊號的一致性。
本研究中我們整理了幾個特徵。在清醒到睏睡的部分，可以看到睏睡時，受測者的眨眼會變慢，而且會比較頻繁，有些受試者會出現眨眼眨一半的情況，而這些現象可以在前額腦電訊號中看到。在閉眼後則會在訊號看到眼動慢波的出現，而當受試者進入睡眠階段N2時，會有sleep spindle（12-14 Hz）的波型出現。而在實驗中我們發現，在閉眼後，受試者很快就會睡著進入N1，而N1的時間也不長，因此，N2的偵測可以作為最後的補救機制。以上特徵可作為未來開發睏睡偵測系統的使用。

This study is the first step towards a sleepiness detecting system based on Forehead-EEG, which disturbs the user much less in daily life. First, we continuously observe the behaviors and signals from alertness to sleepiness and asleep. Then we find some different patterns in the transition of each state. After that, we would grab some patterns could be used in the Forehead-EEG signal. However, the first thing we should confirm is the applicability and feasibility of the Forehead-EEG signal.
To confirm the applicability of the signal, we observe both the video recorded by the camera and the physiological signals. Verifying the feasibility of the signal, we compare the phenomenon observed in video and signal. Besides, we also compare the patterns between Forehead-EEG signal and EEG signal, as ground truth in each stage after eye-closure.
In the study, we conclude some patterns that could be used in the detecting system based on Forehead-EEG. First, blink patterns such as blinking duration and blinking rate changes from alertness to sleepiness. Second, the slow eye movement is observed after closing eyes. The last one, sleep spindle (12-14 Hz) in stage N2 can be the last-ditch attempt to rouse the user, while close wake and stage N1 are short that we have found as scoring stages in the study.

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