完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | 王潔明 | en_US |
dc.contributor.author | Wang, Jie-Ming | en_US |
dc.contributor.author | 林進燈 | en_US |
dc.contributor.author | 邵家健 | en_US |
dc.contributor.author | Lin, Chin-Teng | en_US |
dc.contributor.author | Zao, John K. | en_US |
dc.date.accessioned | 2014-12-12T01:58:10Z | - |
dc.date.available | 2014-12-12T01:58:10Z | - |
dc.date.issued | 2011 | en_US |
dc.identifier.uri | http://140.113.39.130/cdrfb3/record/nctu/#GT079930503 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/49992 | - |
dc.description.abstract | 在長時間而單調的開車環境下,駕駛人員很容易出現打瞌睡的情形。在許多的車禍事故當中,開車打瞌睡被認為是主要的原因之一。為了預防開車打瞌睡所造成的嚴重後果,許多研究致力於尋找打瞌睡相關的腦波變化,進而設計相關之演算法以開發瞌睡偵測相關的設備。然而,對於大腦在意識轉變的過程中不同腦區間的互動卻很少被討論到。因此,本論文著重於探討駕駛人員從清醒到瞌睡以及瞌睡後清醒的過程中腦內訊號傳遞網絡的改變。本研究共有十二位受試者參與模擬夜間高速公路動態的虛擬實驗,實驗中會給予受試者事件相關的偏移任務。受試者的腦波訊號會藉由獨立成分分析取得感興趣的腦區,再以部分直接相關性(partial directed coherence, PDC)的分析方法探討不同意識狀態下腦內之有效連結的改變。研究結果顯示,當受試者處於清醒的駕駛狀態下,在α頻帶的後頂葉皮質會影響紋外皮層;另外,也發現到在θ以及α頻帶的紋外皮層會去影響前額葉皮質。這兩條訊息流的出現代表視覺空間專注(visuospatial attention)的維持及對事件的預測。在轉換時期的駕駛狀態下,從前額葉皮質傳出的訊息流是最強的(所有的頻帶現象一致),這代表受試者似乎需要花更多的努力去維持專注力。其中,由前額葉皮質傳到前運動皮質的訊息流有顯著的上升,我們推測是與受測者將專注力轉移到維持眼睛的動作有關。當受測者進入瞌睡時期的駕駛行為後,與專注及注意相關的訊息流消失了,這代表受測者已經沒有能力專注在開車事件上。另外在瞌睡後清醒的時期,雖然受測者的反應時間與清醒時期相同,但是從腦內網絡的角度來看,大腦的活動已經明顯的改變了。有趣的是,瞌睡後清醒時期的腦內網絡與轉換時期的腦內網絡非常相似。 | zh_TW |
dc.description.abstract | Drowsy driving is one of the major factors leading to traffic accidents, especially occurring in a monotonous environment, the night-time driving, or after long-term driving. To avoid the occurrence of drowsy driving, a considerable number of studies attempted to develop an in-vehicle protocol via monitoring the electroencephalogram (EEG) features of drowsiness. One of the promising measures to evaluate the cognitive state is the change of EEG power spectra. However, most of previous literatures focused on the neurocognitive characteristics on separate brain regions, the human brain network in response to the cognitive transition from alertness to drowsiness is yet poorly understood. To address this issue, this study applied independent component analysis and partial directed coherence to show the change of effective connectivity between distributed brain regions under different vigilance levels, including alertness, transition, drowsiness, and abrupt-awake, during the simulated driving. The results of alpha coupling showed that the extrastriate cortex sent a causal outflow to the anterior region and received a causal inflow from the posterior region while being alert, compared to being drowsy. Regarding the transition state, the anterior region played a major source to affect the rest of the brain region with a cross-frequency coupling, and the connectivity magnitude had a relatively large causality, compared to other vigilance levels. Most of causal magnitudes declined as subjects progressed into a drowsy state. Interestingly, the subjects enabled a short reaction time in response to traffic events when they abruptly awakening from the drowsy state, however, the causal magnitude climbed to the level as the transition state, rather than the alert state. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | 腦電波 | zh_TW |
dc.subject | 開車打瞌睡 | zh_TW |
dc.subject | 專注力 | zh_TW |
dc.subject | 有效連結 | zh_TW |
dc.subject | Granger 因果關係 | zh_TW |
dc.subject | 獨立成分分析 | zh_TW |
dc.subject | EEG | en_US |
dc.subject | Drowsy driving | en_US |
dc.subject | Attention | en_US |
dc.subject | Effective connectivity | en_US |
dc.subject | Granger causality | en_US |
dc.subject | Independent component analysis | en_US |
dc.title | 探討駕駛人員腦內網路之有效連結在不同意識狀態下的改變 | zh_TW |
dc.title | Study of Effective Connectivity in Human Brain Network under Drivers’ Different Arousal Levels | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | 生醫工程研究所 | zh_TW |
顯示於類別: | 畢業論文 |