Abstract

Brain-Computer Interface (BCI) enhances the capability of a human brain in communicating and interacting with the environment directly. BCI plays an important role in natural cognition, which concerns the studies of brain and behavior at work for enhancing or restoring cognitive functions. Many people may benefit from BCI, which facilitates continuous monitoring of fluctuations in cognitive states under monotonous conditions in workplace or at home. People who suffer from episodic or progressive cognitive impairments in daily life can also benefit from BCI. In this talk, I will first introduce the current status of BCI and its major obstacles: lack of wearable EEG devices, various forms of noise contamination, user/circadian variability, and lack of suitable adaptive cognitive modeling. I will then introduce some methodologies to overcome these obstacles, including discovering the fundamental physiological changes of human cognitive functions at work and then utilizing these main bio-findings and computational intelligence (CI) techniques to monitor, maintain, or track human cognitive states and operating performance. In the second part of my presentation, I will introduce an innovative BCI-inspired research domain called Cyber-Brain-Physical Systems. Some future research directions in this domain will be explored and discussed, including BCI-embedded wearable computing, BCI-based neuro-prosthesis and assistive devices, wearable cognitive robots, and BCI-empowered training. The potential real-life applications of BCI on various aspects of training/education, healthcare, rehabilitation, and medical treatment will also be introduced and discussed.

Bio

Dr. Chin-Teng Lin received the B.S. degree from the National Chiao-Tung University (NCTU), Taiwan in 1986, and the Master and Ph.D. degrees in Electrical Engineering from Purdue University, West Lafayette, Indiana in 1989 and 1992, respectively. He is currently Chair Professor of Electrical and Computer Engineering and Director of Brain Research Center, National Chiao-Tung University. He is also International Faculty of the University of California at San Diego since 2012 and Honorary Professorship of the University of Nottingham since 2014.

Dr. Lin's research focuses on machine-intelligent systems, including algorithm development and system design. He has published over 190 journal papers, and is the coauthor of Neural Fuzzy Systems (Prentice-Hall) and author of Neural Fuzzy Control Systems with Structure and Parameter Learning (World Scientific). Dr. Lin has been serving as Editor-in-Chief of IEEE Transactions on Fuzzy Systems since 2011, and has served on the Board of Governors of IEEE Circuits and Systems Society, IEEE Systems, Man, and Cybernetics Society, and IEEE Computational Intelligence Society. Dr. Lin is an IEEE Fellow.