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研究生:林君玲
研究生(外文):Lin, Chun-Ling
論文名稱:視覺動作追蹤任務中觸覺回饋輔助之生理變化
論文名稱(外文):Physiological Correlates of Haptic Feedback in a Visuomotor Tracking Task
指導教授:林進燈林進燈引用關係
指導教授(外文):Lin, Chin-Teng
學位類別:博士
校院名稱:國立交通大學
系所名稱:電控工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:104
中文關鍵詞:觸覺回饋輔助腦電波事件相關頻譜擾動事件相關電聚合現象因果關係
外文關鍵詞:haptic feedbackelectroencephalograph (EEG)electroencephalograph (EEG)event-related spectral perturbation (ERSP)event-related coherence (ERCOH)granger causality (GC)
相關次數:
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  • 收藏至我的研究室書目清單書目收藏:1
本研究主要探討在視覺動作追蹤的任務中,觸覺回饋輔助如何影響運動過程的效能表現以及大腦的動態變化。為了避免生理現象的個體差異,本研究分別設計了兩個實驗來分別探討觸覺回饋輔助對於運動過程的效能表現以及大腦的動態變化的影響。在兩個實驗的過程中,觸覺回饋輔助會以軌跡偏差的狀況給於相對的回饋輔助。而在實驗二中,在給於觸覺回饋輔助的同時,也會量測腦波訊號electroencephalogram (EEG)。並運用獨立成分分析 (Independent component analysis)將所收錄的腦波訊號分離並得到不同的腦區來源。再利用聚集分析(Clustering analysis)比較分析受測者之間的腦區來源。 再者,各腦區來源採取事件相關頻譜擾動(event related spectral perturbation, ERSP)、事件相關電聚合現象 (event-related coherence, ERCOH) 和因果關係 (granger causality, GC) 的分析方法來比較當實驗具有觸覺回饋輔助和沒有觸覺回饋輔助情況下的大腦的動態變化。實驗一結果證實觸覺回饋輔助的確可以有效改善視覺動作追蹤的效能。實驗二結果顯示在有觸覺回饋輔助的情況下,腦區位於右運動區腦波均會呈現較大的Alpha波的抑制。腦區位於左前額骨中間區、左運動區、右運動區和頂葉區的腦波均呈現較大的Beta波的抑制。腦區位於左前額骨、左運動區和右運動區的腦波均呈現gamma波的抑制。相反的,腦區位於右枕骨則呈現了較少的Beta波的抑制。事件相關電聚合現象和因果關係的結果顯示在具有觸覺回饋輔助下,其腦波的聚合結果和因果關係都會呈現將高的相關性。本研究提供了一個新的觀點來觀察觸覺回饋輔對於腦的動態變化的影響,並提出觸覺回饋輔可能是一個工具可用來改善人們在運動學習過程中的效能表現。
This study investigates the temporal behavioral performance and brain dynamics associated with haptic feedback in a visuomotor tracking task. In order to avoid the individual differences in physiological activity, the present study designs two experiments to investigate the differences in motor performance and brain activities between visuomotor tracking in both the presence and absence of haptic guidance, separately. In two experiments, haptic feedback with deviation-related forces was used throughout tracking experiments. In second experiment, subjects' behavioral responses and electroencephalogram (EEG) data were simultaneously measured. Independent component analysis was employed to decompose the acquired EEG signals into temporally independent time courses arising from distinct brain sources. Clustering analysis was used to extract independent components that were comparable across participants. The resultant independent brain processes were further analyzed via time-frequency analysis (event-related spectral perturbation, ERSP), event-related coherence (ERCOH) and granger causality (GC) to contrast brain activity during tracking experiments with or without haptic feedback. The results of behavioral experiment demonstrated that the tracking performance in epochs with haptic feedback were significantly smaller than in those without feedback. In the second experiment, across subjects, in epochs with haptic feedback, components with equivalent dipoles in or near the right motor region exhibited greater alpha band power suppression. Components with equivalent dipoles in or near the left frontal, central, left motor, right motor, and parietal regions exhibited greater beta-band power suppression, while components with equivalent dipoles in or near the left frontal, left motor, and right motor regions showed greater gamma-band power suppression relative to non-haptic conditions. In contrast, the right occipital component cluster exhibited less beta-band power suppression in epochs with haptic feedback compared to non-haptic conditions. The results of ERCOH and GC analysis of the six component clusters showed that there were significant increases in coherence and directed transfer function (dDTF) values between different brain networks in response to haptic feedback relative to the coherence and dDTF values observed when haptic feedback was not present. The results of this study provide novel insight into the effects of haptic feedback on the brain and may aid the development of new tools to improve the performance of visuomotor task.
Chinese Abstract i
English Abstract iii
Acknowledgements v
Table of Contents vi
List of Figures ix
Chapter 1. Introduction 1
1.1. BACKGROUND 1
1.2. MOTIVATION 3
1.3. AIM OF THIS STUDY 5
Chapter 2. Behavioral Performance of Haptic Feedback in a Visuomotor Tracking Task 7
2.1. METHODS 7
2.1.1. Subjects 7
2.1.2. Experimental Equipment 7
2.1.3. Experimental Paradigm 12
2.1.4. Behavioral Data Acquisition 16
2.1.5. Behavioral Data Analysis 16
2.1.6. Statistical Analyses 17
2.2. BEHAVIORAL EXPERIMENT RESULTS 18
2.2.1. Behavioral Performance in Training Session 18
2.2.2. Training Effect of Haptic feedback on Later Evaluation Session 20
2.3. DISCUSSIONS 22
Chapter 3. EEG correlates of haptic feedback in Visuomotor Tracking Task 26
3.1. METHODS 26
3.1.1. Subjects 26
3.1.2. Experimental Equipment 26
3.1.3. Experimental Paradigm 26
3.1.4. Data Acquisition 28
3.1.5. Behavior Data Analysis 29
3.1.6. EEG Data Analysis 29
3.1.6.1. Independent Component Analysis 32
3.1.6.2. Time-Frequency Analysis and Event-Related Spectral Perturbations (ERSPs) 36
3.1.6.3. Event-Related Coherence (ERCOH) 39
3.1.6.4. Granger Causality (GC) 39
3.1.7. Statistical Analyses 44
3.2. RESULTS 46
3.2.1. Comparison of Behavioral Performance between Epochs with and without Haptic Feedback 46
3.2.2. EEG Dynamics Correlated with Haptic Feedback 47
3.2.2.1. Spectral Changes under Different Conditions 48
3.2.2.2. Event-related coherence (ERCOH) between Different Component Activities 53
3.2.2.3. Granger Causality (GC) between Different Component Activities 55
3.3. DISCUSSIONS 57
3.3.1. EEG Spectral Changes Associated with Haptic and Non-haptic feedback 58
3.3.1.1. Cue Period 58
3.3.1.2. Task Periods 59
3.3.2. Functional Connectivity between Different Brain Regions with Haptic Feedback 65
3.3.2.1. Delta Band 66
3.3.2.2. Theta Band 67
3.3.2.3. Alpha Band 68
3.3.2.4. Beta Band 69
3.3.2.5. Gamma Band 72
3.3.3. Effective Connectivity between Different Brain Regions with Haptic Feedback 73
3.3.3.1. Delta and Theta 74
3.3.3.2. Alpha Band 75
3.3.3.3. Beta Band 76
3.3.3.4. Gamma Band 78
Chapter 4. Conclusions 81
Chapter 5. Future works 83
References 85
Appendix: Experimental questionnaire 97
Vita 103
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