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dc.contributor.author曾俊穎zh_TW
dc.contributor.author林進燈zh_TW
dc.contributor.author張志永zh_TW
dc.contributor.authorTseng, Chun-Yingen_US
dc.contributor.authorLin, Chin-Tengen_US
dc.contributor.authorChang, Jyh-Yeongen_US
dc.date.accessioned2018-01-24T07:42:06Z-
dc.date.available2018-01-24T07:42:06Z-
dc.date.issued2017en_US
dc.identifier.urihttp://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT070360039en_US
dc.identifier.urihttp://hdl.handle.net/11536/142379-
dc.description.abstract交通事故是造成死亡的其中一個主要原因,而過去幾年來,逐漸攀升的車禍事件確實是一個很嚴重的問題。過去的研究便指出,駕駛的行為和表現會大大地影響了行車的安全。於是,找尋生理資訊與駕車表現的關係就顯得益加重要。先前的研究會在模擬駕駛實驗中,觀察特定腦區特定波段的腦波變化與開車表現的關係; 另外,有些研究則提出腦區間連結性的變化與警覺性的改變有關聯。除此之外,有文獻更進一步發現,疲勞會影響腦波與駕車表現之間的關係。然而,疲勞是否也會影響腦區間資訊流波動與駕駛表現的關係仍尚未釐清。因此,此實驗利用腕動計,長期的追蹤17位受測者的疲勞狀況,並分別在不同的疲勞程度下進行車道偏移駕車實驗。我們計算這些不同疲勞狀態下的駕駛者腦波的轉置熵做為腦區連結性的指標。在觀察腦區連結性變化與駕車表現的關係中,在中,低的疲勞程度,隨著駕駛的反應時間由快到慢,可以發現連結性有倒U字型與偏移倒U字型的趨勢。在各個疲勞程度,隨著駕駛的反應時間由快到慢,連結性會有不同種類的下降趨勢。觀察低疲勞度到高疲勞度的腦區連結性變化則可發現,從低疲勞度到高疲勞度,額葉腦區的連結性減弱,後腦區的連結性增加。本研究顯示出不同疲勞程度下之受測者,大腦連結性與駕車表現的關係會隨之不同。此研究結果可確立疲勞對駕駛行為表現與其大腦連結性關係之影響。zh_TW
dc.description.abstractTraffic fatalities are one of the leading causes of death in the world. The motor vehicle crash was a serious problem in the past decade. Previous research has suggested that driving behavior and performance played an important role in driving safety. Therefore, a comprehensive understanding of the neurophysiological makers of declining driving performance during driving is significant. Several studies have focused on the change of spectral power in specific brain regions during simulated driving. Another research suggested that the change of brain connectivity in a specific cortico-cortical pathway may also be a sensitive neurophysiological signature for changes in alertness. Additionally, previous studies have stated that the fatigue would change the relationship between the EEG spectral power and behavior during driving. Based on the research above, we wanted to identify the effect of realistic fatigue on brain connectivity-behavior relationship during driving. Thus, in the study, we used the actigraphy device to access the fatigue level of 17 subjects. When the fatigue met the criterion levels, subjects would be asked to participate in the lane keep task. The EEG data were divided into three groups based on different levels of fatigue. We calculated the Transfer entropy of the EEG data to get the effective connectivity of each subject. The result showed that inverted-U shape change of connectivity was founded from high performance to poor performance only in low- and median-fatigue groups. The result demonstrated that different kinds of decreasing shape of connectivity magnitude from high performance to poor performance appeared in different groups. We observed that there was shift inverted-U shape in low- and median-fatigue groups. Additionally, we observed the connectivity difference between low- and high-fatigue groups. The result showed that the magnitude of connectivity decreased at the frontal region and increased at the occipital region form the low- to high-fatigue groups. In a nutshell, these results showed that different levels of fatigue would affect the relationship between brain connectivity and the behavior during driving.en_US
dc.language.isoen_USen_US
dc.subject疲勞zh_TW
dc.subject駕駛zh_TW
dc.subject腦電波zh_TW
dc.subject行為表現zh_TW
dc.subject大腦連結性zh_TW
dc.subject轉置熵zh_TW
dc.subjectfatigueen_US
dc.subjectdrivingen_US
dc.subjectelectroencephalographyen_US
dc.subjecttask performanceen_US
dc.subjectbrain connectivityen_US
dc.subjecttransfer entropyen_US
dc.title疲勞駕駛者之腦電波資訊流變化zh_TW
dc.titleEEG Information Transfer Changes on Fatigue Driversen_US
dc.typeThesisen_US
dc.contributor.department電控工程研究所zh_TW
Appears in Collections:Thesis