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姓名	蔡昀安(Yun-An Tsai)  查詢紙本館藏	畢業系所	機械工程學系
論文名稱	不同環境音下之腦電波特徵分析
檔案	[Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 ( 永不開放)
摘要(中)	本研究透過人因實驗，在不同聲音環境下紀錄受試者在休息以及專注遊玩電腦遊戲下的專注力相關之生理及心理效應，包括腦波訊號擷取、工作績效評估，以及受試者的主觀評量。並藉由訊號處理分析受試者的腦波資料，提取包含碎形維度、近似熵、希爾伯特-黃轉換(HHT)後的邊際頻譜作為分類的特徵，配合分類器如接受者操作特徵曲線(ROC curve)或支持向量機(SVM)進行不同情境間資料的訓練及分類，判別受試者在各個情境間的腦波的差異狀況。計算出分類正確率、接受者操作特徵曲線的AUC值，並且比較各種分類結果，找出適合的特徵以及分類方法。
摘要(英)	This research uses human factors experiments to record the physical and psychological effects of the participants’ concentration during rest and playing computer games in different sound environments. The brainwave data of the participants were analyzed by fractal dimension, approximate entropy, and Hilbert-Huang transform (HHT) into the classifiers, including receiver operating characteristic (ROC curve) and support vector machine (SVM). They are used to train and classify data between different situations, and to distinguish the differences in the brainwaves of participants in each situation. By calculating the classification accuracy and the AUC value of the ROC curve and comparing various classification results, we can figure out suitable attributes and classification methods.
關鍵字(中)	★ 腦電圖 ★ 專注力 ★ 碎形維度 ★ 希爾伯特-黃轉換 ★ 支持向量機	關鍵字(英)	★ EEG ★ concentration ★ fractal dimension ★ Hilbert-Huang transform ★ support vector machine
論文目次	摘要 I ABSTRACT II 誌謝 III 目錄 IV 圖目錄 VII 表目錄 IX 一、 緒論 1 1-1 研究目的與動機 1 1-2 論文架構 1 二、 文獻回顧 3 2-1 腦波簡介 3 2-2 腦波的特徵萃取 8 2-3 腦電波特徵與專注、休息情境分類 11 2-4 環境噪音與專注度 11 三、 研究方法 13 3-1 碎形維度(FRACTAL DIMENSION, FD) 13 3-2 近似熵(APPROXIMATE ENTROPY, APEN) 15 3-3 希爾伯特-黃轉換(HILBERT-HUANG TRANSFORM, HHT) 17 3-4支持向量機(SUPPORT VECTOR MACHINE) 21 3-5 交叉驗證(CROSS-VALIDATION) 26 3-6 接受者操作特徵曲線(ROC CURVE) 27 四、實驗架構與專注力遊戲 31 4-1 腦機介面 (BRAIN-COMPUTER INTERFACE, BCI) 31 4.2 實驗設計 32 五、實驗數據分析流程 38 5-1 數據收集 38 5-2 數據分析 39 六、實驗結果及比較 44 6-1 ROC曲線分析結果 44 6-2 SVM分析結果 56 6-3 分析結果統整 67 6-4 不同情境下遊戲成績 70 6-5 主觀問卷結果 73 七、結論與未來展望 74 參考文獻 76 附錄一 主觀評估問卷內容 82
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指導教授	陳世叡 陳怡君(Shih-Jui Chen Yi-Chun Chen)	審核日期	2021-8-27
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