臺灣博碩士論文加值系統

瞌睡容易使駕車行為產生失常或失誤，致使瞌睡駕駛成為近十年造成嚴重死亡車禍的主要原因之一。先前研究利用虛擬實境進行車道偏移駕車作業，並同步量測受測者的腦電波訊號，來了解大腦與行為之關係，並建立瞌睡駕駛之模型。疲勞是造成瞌睡駕駛的主要原因，然而，疲勞影響大腦與行為之關係尚未清楚，因此，本研究開發每日取樣系統結合客觀腕動計與主觀問卷，對17位受測者之疲勞狀態進行長期的觀察與記錄，並分別在不同疲勞程度之下進行車道偏移駕車作業。在駕駛行為的分析中，可發現反應時間隨疲勞程度上升而增加。在分析車道偏移發生前之腦電波訊號後發現：在中、低疲勞程度之下，大部分腦區的θ與α頻帶能量會隨反應時間增加而上升；相較於中、低疲勞程度，在高疲勞程度之下，隨反應時間增加，後側腦區θ頻帶能量的上升更為明顯，此外，α頻帶能量可發現倒U型趨勢。本研究顯示出不同疲勞程度下之受測者，大腦與行為之關係會隨之不同。此研究結果可對了解瞌睡駕駛與其模型的開發產生重大影響。

Drowsiness can impair task performance and increase behavioral lapses during driving, leading to becoming one of the main causes of fatal car crashes in the past decade. Previous studies have systematically established the brain-behavior relationship through the electroencephalography (EEG) signals recorded from human subjects when they performed a lane-keeping task in a simulated driving environment. Fatigue is the main cause of drowsy driving. However, the effect of fatigue on brain-behavior relationships is unclear. Thus, in this study, we developed the Daily Sampling System integrated with actigraphy and questionnaires to longitudinally assessed and tracked objective and subjective fatigue level of 17 subjects, respectively. When the fatigue met the criterion levels, subjects would be asked to participate in the driving experiment. The behavioral results showed that the reaction time (RT) in response to the deviation event increased with increased fatigue. The pre-stimulus brain activity showed that EEG theta and alpha powers of most of the brain regions observed in low- and median-fatigue groups increased as the RT increased. In the high-fatigue group, the theta power of posterior brain regions dramatically increased with the increased RT as compared with those in low- and median-fatigue groups. Additionally, the alpha power of the occipital regions showed an inverted U-shaped change which was observed only in the high-fatigue group. Taken together, fatigue significantly affects the brain-behavior relationship. Such findings could have major implication for understanding fatigue in drowsy driving and its model.

Chinese Abstract i
English Abstract ii
Acknowledgement iii
Table of Contents iv
List of Tables vi
List of Figures vii
Chapter 1 Introduction 10
1.1 Brain-Behavior Relationships in Drowsy Driving 10
1.2 Statement of the Problem 12
1.3 Aim of this Study 14
Chapter 2 Materials and Methods 15
2.1 Participants 15
2.2 Daily Sampling System 15
2.2.1 Mobile application development 15
2.2.2 Self-reporting questionnaires 18
2.2.3 Actigraphy monitoring device 21
2.2.4 Fatigue level determination 22
2.3 Virtual Driving Experiment 23
2.3.1 Immersive driving environment 23
2.3.2 Lane-keeping task 24
2.3.3 Experimental protocol 26
2.4 Behavioral and EEG Data Recording 27
2.5 Data Processing and Analysis 29
2.5.1 EEG data preprocessing 29
2.5.2 Artifact removal 31
2.5.3 Independent component analysis 32
2.5.4 EEG spectral power estimation 33
2.6 Statistical Analysis with Hierarchical Linear Modeling 35
Chapter 3 Experimental Results 38
3.1 Relationship among Objective and Subjective Measures of Fatigue 38
3.1.1 Daily variations across five months 38
3.1.2 Repeated experimental sessions 40
3.2 Comparison of Task Performance between Different Levels of Fatigue 47
3.3 Resting-State EEG Activities across Different Levels of Fatigue 48
3.4 Brain-Behavior Relationships across Different Levels of Fatigue 49
Chapter 4 Discussion 58
4.1 Effect of Fatigue on Psychometric Response Scale and Task Performance 58
4.2 Effect of Fatigue on Resting-State EEG Activity 60
4.3 Effect of Fatigue on Brain-Behavior Relationships 61
Chapter 5 Conclusions 63
References 65
Appendix 70

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