結合生物反饋之新世代腦機介面及其在移動載具控制之應用---總計畫

Abstract

近幾年來，跨領域合作及基礎與應用結合的研究已成為二十一世紀科技發展的潮流，而有別於傳統的神經與肌肉系統之通訊與控制管道，透過腦波訊號的分析、特徵擷取與命令轉譯來進行機構控制的腦機介面(Brain-Computer Interface) 儼然成為人機互動的新模式。腦機介面除了提供神經或肢體受創的人另一種與外界溝通的機會與管道外，其未來的應用更包含教育學習、臨床治療、認知功能強化，失能警示等不同層面，而讓科技更貼近人類的生活必須。然而腦機介面的系統效能是否能有效提升，成為其未來實用化與生活化的關鍵課題。此系統與傳統控制問題最大的差別在於使用者本身即位於控制迴路中，因此腦機界面效能的提升除了改善機構的控制法則外，腦電波生理特徵的強化與擷取則扮演更重要與關鍵的角色。此三年期整合計劃將藉由微電子、電機資訊，醫學資訊與工程等跨領域專家的合作，結合適用於開放環境之腦電訊號感測系統與多面向的生物反饋機制以開發新世代之腦機介面系統，並應用於移動載具控制，達成應用腦機介面於日常生活與產業應用的目標。由於目前大多數的腦電波生理感測器多僅適用於封閉與控制環境中，因此本計畫將開發開放式生理訊號擷取感測器（Bio-Sensors）以在日常環境中擷取高感度的腦電生理訊號，並設計即時訊號處理晶片與嵌入式整合系統作為腦機介面載台。此外有別於傳統之二元式腦機介面，我們將開發多重命令之運動想像腦機介面，以產生控制命令進行移動載具作控制。為了提升腦機介面之控制效能，我們將開發多面向生物反饋技術，利用反饋式學習與訓練，增進使用者本身之空間巡行能力、精神專注力以提升其腦電訊號特徵之強度與淨度，以大幅提升腦機介面之系統效能。基於上述的各項工作，我們以五個子計劃來進行：子計劃一為智慧型感測系統單晶片設計與嵌入式無線生醫平台開發，負責進行複合生理訊號感測系統單晶片的設計與製作，同時也利用設計出來的晶片進行嵌入式系統整合。子計劃二將探討分心效應對於行為與腦電波活動的影響，並透過多面向生物反饋技術適時給予使用者警告語提醒；子計劃三將探討在想像運動下的腦波反應，並為腦機介面建立控制模型；子計劃四將以機器視覺技術協助車輛或機具的控制，使其準確效能提高；當使用者本身已迷失方向或不專心，將嚴重影響腦機介面的系統效能，因此子計劃五將探討方向感迷失與分心效應對於行為與腦電波活動的影響，並透過多面向生物反饋技術調整使用者之空間巡行策略，並提升使用者的專注力，使整體腦機介面控制能臻完美。整合計劃將結合六個子計劃所發展的結合生物反饋之新世代腦機介面，並實地進行移動載具之控制驗證。此研究預期將是微電子、電機資訊，醫學資訊與工程之跨領域的成功整合。對控制科技領域具有觀念與應用突破的貢獻，提升我國生醫儀器產業水準，未來將可廣泛應用於教育學習、腦功能病變治療、老人認知功能強化，高度專注力工作的警示回饋等，讓科技更貼近人類的生活必須，增進生活之幸福與安全感。

Current brain computer interface (BCI) systems provide users with communication channels that do not depend on peripheral nerves and muscles. Specifically, the BCI system use electroencephalographic (EEG) activities recorded at the scalp to control or operate external devices. The central processes in each BCI included two major steps. First, the BCI systems analyzed and extracted the significant features from the electrophysiological inputs, and then BCI systems encoded those results into commands and express them in device control. However, there are three limitations at present BCI systems that critically affected the system performance. First, the bio-sensors for BCI systems were designed for a well controlled recording environment. Second, most BCI systems used the binary control model to operate external devices. The above two limitations will restrict the applications of BCI technologies. Third, the performance of BCI was greatly influenced by the user’s performance and attention since the user was included into control loops of the BCI system. Therefore, the main goal for this project is integrating the Micro Electro Mechanical systems (MEMS), computer science, bioinformatics and electrical engineering to develop a new BCI system that can be easily applied on a moving vehicle. The new system will include high fidelity and sensitivity EEG sensors with an intelligent multi-stream physiological signal recording and analysis system. In addition, the system will control the moving vehicle with multi-comments that extracted from the motor imagery. Furthermore, it will incorporate a multi-dimensional biofeedback control loop to increase the user’s navigated performance or attention that can get better signal to noise ratios of EEG signals. This project will be the first time to successfully integrate the Micro Electro Mechanical Systems (MEMS), computer informatics, bioinformatics and engineering. Both the concept and its application for control technology are revolutionary. In addition, such innovation will make a significant contribution to promoting the biomedical industry, and widespread applications on education, clinical treatment, enhancing the elders’ cognitive function and the safe warning system for people who needed to highly concentrated on their work.