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系統識別號 U0026-2401201112024300
論文名稱(中文) 以DSP晶片系統實現運動想像為依據的大腦人機介面之設計
論文名稱(英文) Motor Imagery Based Brain Computer Interface Implemented On a DSP System
校院名稱 成功大學
系所名稱(中) 電機工程學系碩博士班
系所名稱(英) Department of Electrical Engineering
學年度 99
學期 1
出版年 100
研究生(中文) 蘇暐迦
研究生(英文) Wei-Chia Su
學號 n2697194
學位類別 碩士
語文別 中文
論文頁數 45頁
口試委員 指導教授-戴政祺
口試委員-黃世杰
口試委員-魏嘉玲
口試委員-楊弘吉
中文關鍵字 腦波  大腦人機介面  數位信號處理 
英文關鍵字 Brain computer interface (BCI)  electroencephalogram (EEG)  digital signal processor (DSP) 
學科別分類
中文摘要 大腦人機介面是一種使用腦波與機器溝通的一種技術,透過非侵入式或侵入式的方式量測到大腦的腦波訊號,並使用大腦人機介面轉換成使用者所要控制的指令。腦波可依其頻率及特性分為α、β、θ、δ、μ等節律,其中大腦的μ(8-12 Hz)頻帶在運動想像時或實際運動時會降低其能量大小,因此可以觀察此能量的變化,計算8-12 Hz能量大小並將結果分為兩類,分別是放鬆與想像狀態,將此兩種狀態對應於LED的暗與亮,做為腦波控制的輸出應用。本論文研究重點在於自行開發基於DSP晶片之腦波分析系統,並用於分析大腦於運動想像下的狀態,觀察其頻譜能量大小,進行腦波訊號的特徵值分類,達到可即時使用腦波控制的功能。期盼本研究可幫助行動不便的人,使他們能使用腦波訊號,就可以達到與外界溝通、自主行動等目的以達到提升生活品質。
英文摘要 The brain-computer interface (BCI), which facilitates communication between human and a machine, can use noninvasive or invasive methods to record electroencephalogram (EEG) signals. The BCI transforms a user’s EEG signals into commands that can be utilized to control a computer or other devices. The EEG signals can be distinguished by their frequencies and characteristics, namely, the α, β, θ, δ and μ rhythms. The EEG activity in the μ (8-12 Hz) frequency bands decreases in amplitude during real or imagined movement, such as imagined movement of the right hand, left hand, or foot. Discriminating between two brain states, such as that associated with imagined right-hand movement and that associated with a relaxed brain, can correspond to the on and off states of a light-emitting diode (LED). This can be used for real-time control with BCI. This work analyzes the characteristic values of EEG by power spectrum method using a self-developed signal analysis system based on a digital signal processor (DSP). The research results can be used to help paralyzed people.
論文目次 摘 要 I
Abstract II
誌謝 III
目錄 IV
表目錄 VII
圖目錄 VIII
第一章 緒論 1
1.1研究背景 1
1.2相關文獻回顧 2
1.3研究動機與目的 3
1.4論文架構 3
第二章 研究背景 4
2.1腦波簡介 4
2.1.1腦波生理概述 4
2.1.2大腦皮質區功能簡介 4
2.1.3腦波頻率與節律分類 5
2.2腦波電位訊號記錄與處理 6
2.2.1腦波電極位置 6
2.2.2腦波組合範式 7
2.3大腦人機介面 8
2.3.1基本架構 8
2.3.2相關的特徵擷取 9
第三章 系統架構與設計 10
3.1系統架構 10
3.1.1系統方塊圖 10
3.1.2電源供應電路 11
3.1.3前端量測電路 13
3.1.4省電型微處理器及相關電路 16
3.1.5開發平台TMS320C6713 DSP Starter Kit ( DSK ) 簡介 18
3.1.6無線模組 20
3.1.7周邊電路 21
3.2腦波處理演算法 22
3.2.1腦波資料處理流程 22
3.2.2腦波資料的預處理 23
3.2.3快速傅利葉轉換 24
3.2.4 K-Nearest Neighbor 分類法 25
3.2.5 程式流程 28
第四章 腦波信號實驗分析結果與討論 30
4.1實驗設計 30
4.1.1實驗流程 30
4.1.2腦波訓練流程 31
4.2實際EEG信號分析 32
4.2.1 睜眼與閉眼實驗結果 32
4.2.2 μ波於運動想像時抑制的特性 34
4.2.3 放鬆與想像狀態的分析 35
4.2即時分析結果與討論 39
第五章 結論與未來發展 41
5.1結論 41
5.2未來展望 41
參考文獻 43
自述 45
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