【電機系書報討論演講訊息】

書報討論網址：http://www.ee.nthu.edu.tw/~ee591000/

演講公告網址：/p/403-1175-2629-1.php

題   目：無線腦機介面開發與應用

Developments of Mobile and Wireless Brain Computer Interface and Its Applications

講   員：柯立偉 教授 (交大生醫與生物工程研究中心)

時        間：2012年11月9日(星期五) 下午2時20分  (2時10分入場)

地        點：資電館B01演講廳
 

Abstract

近年來在醫學診斷和神經生物學研究中，腦電波訊號(Electroencephalogram, EEG)已成為非常有用的非侵入式生理訊號工具，主要因為它能在時域上提供較高的訊號解析度，直接反映出神經細胞群體中動態的變化。在所有量測大腦造影的醫療工具中，量測腦電波訊號最不受任何限制，因為在量測過程中，受試者不需受到固定身體和保持頭不動等限制。然而，若將現今市面上的腦波監測系統應用到日常生活中卻會深深受到許多限制，例如：需在頭皮上塗抹導電膠才能量測腦電波訊號，系統缺乏高精確度的量測，即時訊號處理和有效去除雜訊等功能，皆是主要腦波監測系統的缺失。本演講將介紹新穎腦機介面(Brain Computer Interface)開發，設計和測試，並如何應用於日常生活環境裡，即使是在多變的環境中做不同的工作任務，亦能直接擷取大腦活動變化。在擷取腦波生理訊號後，訊號處理尤為重要，因此將接著介紹如何進行腦波訊號源擷取分離(Brain Source Separation)，事件相關誘發電位(ERP)和事件相關頻譜動態分析(ERSP)等分析，並結合計算智慧型技術(Computational Intelligence)開發即時認知狀態估測系統，以交大腦科學研究中心建構之環繞式虛擬實境動態駕駛平台為實例進行探討受試者駕車時的認知精神狀態的腦動態變化。

Biography

Li-Wei (Leo) Ko received the B.S. degree in mathematics from National Chung Cheng University in 2001, the M.S. degree in educational measurement and statistics from National Taichung University in 2004, and the Ph.D. degrees in Electrical Engineering from National Chiao Tung University (NCTU), Taiwan, in 2007. He currently is an assistant professor in Department of Biological Science and Technology, and Brain Research Center (BRC) in NCTU. He is also the visiting scholar at Institute for Neural Computation in University of California, San Diego (UCSD). In academic service, he serves as the Associate Editors of IEEE Transactions on Neural Networks and Learning Systems in IEEE Computational Intelligence Society (CIS), and Journal of Neuroscience and Neuroengineering. He is also the committee members of Neural Network Technical Committee and Fuzzy Systems Technical Committee in IEEE CIS. His primary research interests are EEG signal processing and applying computational intelligence technologies to analyze neural activities associated with human cognitive functions and develop the mobile and wireless brain machine interface in unconstrained, actively engaged human subjects in daily life applications. Relevant research fields cover neural networks, neural fuzzy systems, machine learning, brain computer interface, and computational neuroscience.

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