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研究生: 徐政煒
Hsu, Cheng-Wei
論文名稱: 應用隨機共振法強化事件相關去同步現象
Enhancing Event Related Desynchronization (ERD) by Using Stochastic Resonance
指導教授: 朱銘祥
Ju, Ming-Shaung
林宙晴
Lin, Chou-Ching
學位類別: 碩士
Master
系所名稱: 工學院 - 機械工程學系
Department of Mechanical Engineering
論文出版年: 2005
畢業學年度: 93
語文別: 中文
論文頁數: 79
中文關鍵詞: 觸覺閥值事件相關去同步隨機共振腦電波圖
外文關鍵詞: stochastic resonance, SR, tactile threshold, EEG, ERD, Event Related Desynchronization
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  •   中風或脊髓損傷常造成大腦失去控制肌肉的能力,使患者的肢體無法自主動作,而人腦與電腦介面系統是幫助患者恢復與外界溝通能力的方法之一。大腦傳遞訊息給電腦,接著電腦判斷訊息並下控制命令給輔具,由輔具來代替患者的肢體,恢復日常生活中的行為能力。事件相關去同步(Event Related Desynchronization)是腦波因神經元不同步活化,造成腦波產生抑制的現象,尤其是mu波和beta波在人自主動作或藉由想像肢體動作都可產生抑制,因此許多研究以此作為輔具的控制源。但抑制現象會因個體產生差異性,影響人腦與電腦介面辨識率。本研究旨在應用隨機共振法以強化常人mu波及beta波抑制,以提升辨識率。藉由增加機械性的雜訊刺激於人體,透過感覺系統傳遞至大腦皮質,當人自主動作使腦波產生抑制的同時,加上雜訊讓抑制量提升,提供人腦與電腦介面更正確的判斷。
      由常人實驗發現,當機械性的隨機刺激,振幅略高於人體觸覺閥值時,發現可找出最佳刺激振幅使mu波和beta波產生最大的抑制量。但過大的振幅,反而使得抑制量減弱。刺激振幅與腦波抑制量的關係呈現鐘形曲線變化。本研究以七位常人的實驗結果證實隨機共振法有可能提升大部分常人腦波的抑制量。

     The paralyzed patients can not voluntarily move their limbs due to the disruption of connection between brain and muscles. Brain-computer interface is one of the methods to assist paralyzed patients to communicate with the external environment. The computer receives information from the brain, and generates control command to prosthesis which substitutes limbs to perform daily work. Event related desynchronization represents the phenomenon that certain brain rhythm is suppressed by some events. Suppression of mu and beta waves by voluntary movements or imagination of voluntary movements can be utilized to control prosthesis. One of the difficulties in using event related desynchronization as the control source is the inter-individual variability. The goal of our study is to enhance the event related desynchronization and to increase the detection rate of movement attempt by using stochastic resonance. Stochastic resonance is a technique to enhance the detection of weak inputs in nonlinear systems. Since the relationship between tactile afferent from skin to the cortex is a complex nonlinear system, it is possible that stochastic noises may enhance the afferent signals and increase the success rate of control command.
     In applying small mechanical stimuli to a subject, the optimum stimulus amplitude, which is larger than the tactile threshold, was found to yield the largest suppression of mu and beta waves. The curve of noise intensity versus suppression of brain rhythm is bell-shaped. The noise intensity with amplitude higher than the optimum amplitude reduces the suppression of mu and beta waves. The experimental results from seven normal subjects confirm that event related desynchronization could be enhanced by stochastic resonance.

    中文摘要 I 英文摘要 II 目錄 III 圖目錄 VI 表目錄 X 符號表 XI 第一章 緒論 1 1-1 研究背景 1 1-2文獻回顧 4 1-2-1 人腦-電腦介面 4 1-2-2 隨機共振法 6 1-3 研究動機與目的 8 1-4 本文架構 9 第二章 方法與實驗 10 2-1 人體感覺系統 10 2-2 實驗系統架構 13 2-2-1 機械性刺激系統與腦波量測系統 13 2-2-2 刺激器設計 15 2-2-3 刺激器數學模型 17 2-2-4 頻率響應模擬 22 2-2-5 腦波訊號處理 24 2-3 實驗設計 27 2-3-1 受測者資料 27 2-3-2 實驗步驟 28 2-3-3 統計分析 30 第三章 結果 31 3-1 未加刺激結果 31 3-2 刺激手掌結果 33 3-2-1 mu波結果 33 3-2-2 beta波結果 38 3-3刺激指尖結果 44 3-3-1 mu波結果 44 3-3-2 beta波結果 49 3-4 統計分析結果 55 3-4-1 刺激手掌統計結果 55 3-4-2 刺激指尖統計結果 60 第四章 討論 63 4-1 手掌與指尖刺激 63 4-2 mu波與beta波 65 4-3 統計結果 67 4-4 生理模型 68 4-4-1 模型建立 68 4-4-2 模擬 72 4-5 人腦與電腦介面應用 74 第五章 結論與建議 75 5-1 結論 75 5-2 建議 76 參考文獻 77

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