在有干擾的虛擬教室環境下 大人小孩的行為表現與腦神經反應的異同

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陳嬿晴(Yan-Qing Chen) 查詢紙本館藏

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資訊工程學系

論文名稱

在有干擾的虛擬教室環境下大人小孩的行為表現與腦神經反應的異同
(Age Difference on Attention under 3D Virtual Reality Environment with Interference)

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摘要(中)

本研究的目的是研究注意力、反應抑制和干擾抑制的年齡差異。在虛擬教室實驗中，受試者配戴頭戴式VR頭盔結合乾式電極的腦電波儀，在3D虛擬教室環境中進行一種注意力測驗(AX-CPT)，並且在測驗期間會無預警地出現視聽覺干擾。我們對腦電波進行分析並使用事件相關電位（ERP）和事件相關光譜功率（ERSP）從行為和電生理學的角度觀察注意力和抑制功能的成熟。從實驗結果可以看出，成人的P3幅度較大，P3和N2潛伏期都比兒童長，說明成人在注意力和抑制方面比兒童成熟。在機器學習方面，在NOGO-D刺激下會得到最好的分類結果，也證明了成人和兒童在抑制功能上有顯著差異。綜合上述，本研究探討了任務表現和腦電圖信號的年齡差異，這樣的研究成果也可以應用於與注意力或抑制發展相關的測試或活動，並將不同年齡層的表現納入考量或基於此做更深入的研究。

摘要(英)

This study investigates the age difference in attention, response inhibition, and interference suppression by performing the AX-CPT task, using HMD-VR with an EEG device under a 3D virtual reality classroom with auditory and visual interference during the task. We intend to observe the maturation of attention and inhibition from a behavioral and electrophysiological perspective using Event-related Potentials (ERPs) and Event-related spectral power (ERSP). It can be seen that the P3 amplitude of adults is larger, and both P3 and N2 latency are longer than children, which means that adults are more mature than children in terms of attention and inhibition. In terms of machine learning, the NOGO-D trials will obtain the best classification results under the NOGO-D trials. It also proved that adults and children have significant differences in inhibitory function. In conclusion, this study explored the age differences in task performance and EEG signals. It can also be applied to tests or activities related to the development of attention or inhibition, designed to consider age differences and further explored.

關鍵字(中)

★ 注意力
★ 抑制
★ 虛擬實境
★ 干擾
★ 腦電波
★ 事件相關電位

關鍵字(英)

★ Attention
★ Inhibition
★ Virtual Reality
★ Interference
★ EEG
★ Event-related potentials (ERPs)

論文目次

Table of Contents
摘要 i
Abstract ii
致謝 iii
Table of Contents iv
List of Figures vi
List of Tables vii
1. Introduction 1
1.1 Attention and its relation to age 1
1.2 Inhibition and its relation to age 2
1.3 Cognitive function and its relation to EEG 2
1.4 P300 and N200 3
1.5 Frequency bands 4
1.6 AX-CPT 5
2. Related Work 6
2.1 Age Difference in Go/NoGo task 6
3. Experimental Method 9
3.1 Equipment and software 9
3.2 Game design and distractors 10
3.3 Participants and EEG acquisition 11
3.4 EEG data processing and feature extraction 12
3.5 Dataset 14
3.6 Statistical analysis and machine learning methods 14
4. Result 17
4.1 Statistical analysis on CPT task performance 17
4.2 Statistical analysis on ERPs 18
4.2.1 The effect of inhibition (i.e., GO-D vs. NOGO-D trials) 18
4.2.2 The effect of distractions (i.e., D vs. ND trials) 19
4.3 Statistical analysis on ERSP 20
4.3.1 The effect of inhibition (i.e., GO-D vs. NOGO-D trials) 20
4.3.2 The effect of distractions (i.e., D vs. ND trials) 22
4.4 ERPs and power spectrum 24
4.5 Classify adults and children 26
5. Discussion 28
5.1 Statistical analysis on CPT task performance 28
5.2 Statistical analysis on ERPs 28
5.3 Statistical analysis on ERSP 29
5.4 ERPs and power spectrum 30
5.5 Classify adults and children 30
6. Conclusion and Future Work 31
Reference 33
Supplementary 1: GO-D vs. NOGO-D -1-
Supplementary 2: D vs. ND -11-

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指導教授

葉士青吳曉光(Shih-Ching Yeh Hsiao-Kuang Wu)

審核日期

2022-9-30

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