臺灣博碩士論文加值系統

突發的緊急狀況對駕駛者而言，常會因反應不及，造成意外的發生。之前的研究(陳諺玄,2013)指出這與大腦抑制機制的運作有極大關係，但對此機制會受到那些因素的影響，尤其現今社會步調快速，人們常處於時間壓力底下，這是否會直接干擾抑制機制的運作，影響車輛控制的能力，尚需進一步地釐清。因此，本研究藉由操弄駕駛終止信號作業的時限以探討時間壓力下，突發狀況發生時，對駕駛者大腦內部抑制機制運作的影響，除了瞭解相對應的行為表現，並利用獨立成分分析方法以及事件相關頻譜擾動分析，觀察相對應之腦電波在頻率和時間上的特徵與變化。。行為結果顯示時間壓力會縮短成功抑制所需的時間。在腦波結果方面則發現，駕駛遭遇緊急狀況時，不管是否有時間壓力，大腦的抑制機制運作與前腦區與中央腦區δ頻帶(1-3Hz)及θ頻帶(4-7Hz)的能量上升有關；但在時間壓力底下，則在前腦區與中央腦區有明顯的β頻帶(13-30Hz)及γ頻帶(30-50Hz)的能量上升。另外，抑制成功會比抑制失敗在中央腦區呈現更大的δ頻帶變化；在時間壓力下，在中央腦區則多了β頻帶及γ頻帶的能量增加。本研究結果顯示: 時間壓力似乎會透過β與γ頻帶，調節抑制機制之運作，促進駕駛者在緊急情況發生時的應變能力。

How to deal with the upcoming emergency situations is a key to avoid car accidents. Previous study (Chen, 2013) used brain imaging to reveal that the efficiency of inhibition function is responsible for copying such situations. However, other factors, such as stress, on driving inhibition are still unknown. Hence, in this study, we aim to get an insight into brain activities of emergency management in stress conditions.
To investigate driver’s brain responses to inhibition function, a modified stop-signal driving task was implemented in a virtual-reality driving environment. The electroencephalography (EEG) was recorded from 16 subjects as they performed the experimental tasks under normal (without time pressure) and stress (with time pressure) conditions. Given a fixed road distance, each subject was instructed to arrive at the finishing line within a limited time under the stress condition. In signal processing, independent component analysis (ICA) and event-related spectral perturbation (ERSP) analysis were applied to investigate the spectral dynamics of independent brain processes.
The behavioral results showed that the stop-signal reaction time (SSRT) was shorter under the stress condition than that under the normal condition. This result indicated that the stress could help to improve the efficiency of inhibition ability. The ERSP results showed that the augmentation of delta (1-3 Hz) and theta (4-7 Hz) powers in frontal and central areas are related to the inhibition mechanism. There is no statistically significant difference between two conditions. However, beta (13-30 Hz) and gamma (30-50 Hz) powers in frontal and central areas increased only in the stress condition. The beta and gamma powers of the central area under the stress condition were significantly higher than those under the normal condition. Because the gamma band is thought to reflect the top down modulation, the time pressure could possibly improve the driving inhibition efficiency by the proactive control which prepares to stop before the signal onset.

Contents
中文摘要 i
Abstract ii
Acknowledgement iii
Contents iv
Tables vi
Figures vii
Chapter 1 Introduction 1
Chapter 2 Literature Review 3
2.1 Stress 3
2.2 Inhibiting Process in Driving 4
2.3 Stop Signal Task 5
2.4 The Aim of The Current Study 6
Chapter 3 Methods 7
3.1 Participants 7
3.2 Experimental Environment 7
3.3 Experimental Procedure 9
3.3.1 Normal Condition – Normal Driving 11
3.3.2 Stress Condition – Driving under acute stress (Time Pressure) 12
3.4 Behavioral and EEG data Recording 13
3.5 Behavioral Data Analysis 14
3.6 EEG Data Analysis 15
3.6.1 EEG Data Preprocess 16
3.6.2 Independent Component Analysis (ICA) 16
3.6.3 Component Selection and Clustering 19
3.6.4 Event Related Spectral Perturbation Analysis 20
3.7 Statistics 22
Chapter 4 Results 24
4.1 Behavioral Data 24
4.1.1 Normal Condition 24
4.1.2 Stress Condition 25
4.1.3 Comparison between Normal Condition and Stress Condition 25
4.2 EEG Data 29
4.2.1 Component Cluster 29
4.2.2 EEG Dynamics 30
4.2.3 ERSPs of Go Trials: Normal Condition and Stress Condition 31
4.2.4 ERSPs of Successful Stop Trials: Normal Condition and Stress Condition 32
4.2.5 ERSPs of Unsuccessful Stop Trials: Normal Condition and Stress Condition 33
4.2.6 Normal Condition: ERSPs between Successful Stop Trials and Unsuccessful Stop Trials 34
4.2.7 Stress Condition: ERSPs between Successful Stop Trials and Unsuccessful Stop Trials 36
Chapter 5 Discussion 38
5.1 Behavioral Characteristics between Normal and Stress Conditions 38
5.2 EEG Characteristics of Go Response between Normal and Stress Conditions 39
5.3 EEG Characteristics of Driving Inhibition between Normal and Stress Conditions 41
5.4 Difference between Successful and Unsuccessful Driving Inhibition in Normal and Stress Conditions 45
Chapter 6 Conclusion 47
Reference 48
Appendix 54

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