臺灣博碩士論文加值系統

近幾年來腦波應用蓬勃發展，腦波研究領域相當熱門，為了研究不同行為中的腦波特徵，如：專注、放鬆、暈眩、睡眠狀態等，因此發展出腦機介面（Brain Computer Interface，簡稱BCI）技術來探討人類潛意識、行為，並將收集到的腦波特徵應用到生活、醫療、教育、精神訓練。目前已經有研究將腦波應用到讓身體癱瘓之患者進行自己進食、打字等，若將腦機介面應用到教育中，能夠讓教師知道學生的專注狀態則能夠增進學習之效果。
因此本研究結合腦機介面與Unity，開發一套專注力應用系統進行專注力訓練實驗，其中腦機介面包含嵌入式系統、藍牙（Bluetooth）裝置等技術，因此系統體積不會過大、方便受測者攜帶。本系統從量測到的腦波資料中擷取β波（Beta波）進行判斷受測者是否為專注狀態，並將其結果應用到遊戲中，實驗結果能夠有效提升受測者的專注力程度。

The application of brainwave becomes a flourishing industry in recent years. The research field of brainwave is quite popular. In order to studying the characteristics of brainwaves in different behaviors, such as concentration, relaxation, dizziness, sleep, etc, Brain Computer Interface (BCI) technology has developed to analysis the human subconsciousness, behavior, and the collected brainwave features can be applied to life, medical care, education, mental training, and so on. According to the reports, the paralyzed patients could eat and type by themselves using BCI. In the education filed, the teacher would recognize whether the student is concentrating or not. Thus, BCI will enhance the learning consequent.
The aim of this research is to develop a system for the concentration training application. The system combines with the Unity game and the BCI which contains of the embedded system and Bluetooth device. The size of the developed system is small. In addition, the system is convenient for testing. The system collects the beta wave from the measured brainwave data, and it can determine whether the user is concentration or not to control the Unity game. The results of this study show that the proposed system can enhance the concentration of people.

目錄
明志科技大學碩士學位論文指導教授推薦書 I
明志科技大學碩士學位論文口試委員會審定書 II
誌謝 III
摘要 IV
Abstract V
目錄 VI
圖目錄 VIII
表目錄 XI
第一章 緒論 1
1.1 研究背景與動機 1
1.1.1 生理訊號 1
1.1.2 腦機介面 4
1.1.3 腦波相關應用與發展 7
1.2 研究目的與方法 8
1.3 論文大鋼 10
第二章 文獻探討 11
2.1 濾波器 11
2.2 儀表放大器 14
2.3 增益放大器 14
2.4 STM32F373RCT6 15
2.5 快速傅立葉轉換 15
2.6 HL-MD08R-C2 16
2.7 STM32F373開發平台 16
2.7.1 STM32CubeMX 17
2.7.2 Keil μvision5 20
2.8 Altium Designer 20
2.9 Unity遊戲開發平台 21
2.9.1 Unity環境介紹 22
2.10 Brain Rhythm 8 23
2.11 OpenVibe 25
2.12 專注力 25
第三章 專注力應用於遊戲 29
3.1 腦機介面電路設計 29
3.1.1 電路圖設計 33
3.1.2 遊戲設計 34
第四章 實驗流程與結果 38
4.1 專注力系統 38
4.2 腦機介面驗證 40
4.3 系統流程 45
4.3.1 前置作業 45
4.3.2 硬體作業 46
4.3.3 系統說明 47
4.3.4 受測結果 51
第五章 結論與未來展望 52
5.1 結論 52
5.2 未來研究與發展 53
參考文獻 54

圖目錄
圖1.1國際10-20腦波電極配置法（a）為左側臉（b）為頭頂[8] 3
圖1.2傳統腦波儀[13] 4
圖1.3導電膠之電極帽[14] 4
圖1.4腦波量測系統區塊圖 5
圖1.5 NeuroSky MindWave耳機[22] 7
圖2.1濾波器頻率響應圖[36] 11
圖2.2被動式低通濾波器 12
圖2.3被動式高通濾波器 12
圖2.4被動式帶通濾波器 13
圖2.5被動式雙T陷波濾波器 13
圖2.6 AD620腳位示意圖[37] 14
圖2.7 OP07腳位示意圖[38] 14
圖2.8 STM32F373RCT6開發板 15
圖2.9 HL-MD08R-C2模組 16
圖2.10新建專案，選擇開發板介面 17
圖2.11 STM32F373腳位設定 18
圖2.12 STM32F373時序設定 18
圖2.13鮑率設定 19
圖2.14編譯程式碼 19
圖2.15 Keil uvision5程式撰寫介面 20
圖2.16 Unity介面示意圖 22
圖2.17 Brain RhythmBrain Rhythm 8[47] 23
圖2.18 BR8量測位置圖 24
圖3.1腦波量測方塊圖 29
圖3.2本研究之低通濾波器 30
圖3.3本研究之高通濾波器 30
圖3.4本研究之雙T陷波濾波器 31
圖3.5 AD620接線圖 32
圖3.6 OP07接線圖 32
圖3.7腦機介面電路圖 33
圖3.8腦機介面電路板佈線圖 33
圖3.9腦機介面實體圖頂層 34
圖3.10腦機介面實體圖底層 34
圖3.11資料分析流程圖 35
圖3.12 Unity加入物件 36
圖3.13 C#程式示意圖 37
圖3.14 Unity按鈕與計分板 37
圖4.1專注力系統架構示意圖 38
圖4.2腦機介面實體接線圖 39
圖4.3示波器顯示結果圖 40
圖4.4 OpenVibe使用介面 41
圖4.5 OpenVibe設定介面 41
圖4.6 OpenVibe模組設定 42
圖4.7 OpenVibe讀取程式 42
圖4.8 BR8與本論文腦機介面配戴方式 43
圖4.9眨眼訊號之比較 43
圖4.10閉眼訊號之比較 44
圖4.11咬牙訊號之比較 44
圖4.12資料分析流程圖 45
圖4.13配戴方式 46
圖4.14腦機介面量測位置圖 46
圖4.15系統首頁 47
圖4.16接收基準值畫面 48
圖4.17專心（射擊）狀態 49
圖4.18不專心（非射擊）狀態 50
圖4.19遊戲結束 50
圖4.20專注力統計圖 51

表目錄
表1.1電極比較表 6
表2.1 BR8規格表[47] 24

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