台北科技大学刘益宏博士学术讲座通知
题目：基于脑波之情绪辨识及脑机接口系统实现
EEG-based Emotion Recognition and Implementation of the Brain-Computer Interface Systems
主讲：刘益宏博士 台北科技大学副教授
时间：2016年3月9日（周三）下午15:00
地点：机电楼1020
主讲人简介：刘益宏自台湾大学取得机械工程博士，目前任教于台北科技大学机械系及机电整合研究所，担任副教授，同时担任台北科技大学典范科大计划推动办公室副执行长。
自2013年起，刘博士担任IEEE SMC学会医疗机电技术委员会共同主席(co-chair of Technical Committee on Medical Mechatronics)，并于2014年荣获IEEE The Most Active Technical Committee Award。刘博士担任多个SCI/EI国际期刊之客座编辑，包括International Journal of Fuzzy Systems (2016)、Mathematical Problems in Engineering (2014)、International Journal of Automation and Smart Technology (2013, 2016)。刘博士担任许多国际研讨会之筹备委员，包括IEEE Int. Conf. SMC之议程委员、2015 Int. Conf. Advanced Robotics and Intelligent Systems (ARIS 2015)之大会议程共同主席，并曾荣获2012 Int. Conf. Mechatronics and Applied Mechanics之Best Paper Award。在台湾方面，刘博士于2015年被聘为台湾财团法人工业技术研究院之特聘研究员(顾问)，并担任2015年台湾科技部控制学门、自动化学门之学门规划委员。刘博士曾于台湾获得不同奖项，包括教育部产业新进设备人才培育计划之103学年度半导体及光电优良教课书选佳作(2014)、科技部自动化学门专题计划成果发表会海报竞赛佳作奖(2014)、自动化光学检测论坛及竞赛年度最佳论文奖(2010)、中国工业工程学会工程论文奖(2006)、教育部影像显示专题实作竞赛最佳实用奖 (2006)。
刘博士之研究领域包括脑机接口、神经义肢、生理讯号回馈复健机器人、机器学习、智能型系统诊断及影像检测等，在这些领域已发表超过80篇之国际期刊及国际研讨会论文，包括IEEE/ASME Trans. Mechatronics、IEEE Trans. Neural Networks、Sensors等期刊。
讲座内容简介：
Emotion recognition based on neurophysiological signals has received increasing attention in many research fields for its great potential in various applications where emotion recognition is required, such as human-robot interaction, healthcare, clinically medical diagnosis, and even in education. Among the neurophysiological signals, electroencephalography (EEG) is consider the most promising and can reflect the inner-most emotional states because emotion perception and regulation of human beings is directly related to the cortex and sub-cortex areas of the brain. However, EEG signal possesses a very low signal-to-noise ratio, and suffers from the volume conduct effect due to non-invasive measurement of brain activity, which suggest the complexity of EEG-based emotion recognition. As a result, EEG-based emotion recognition has been considered a challenging topic in the brain-computer interface (BCI) community. In this talk, state-of-the-art EEG-based emotion recognition methods will be introduced, as well as some experimental procedures for emotion induction and emotional EEG acquisition. In addition to emotion recognition from EEG, its application in the detection of major depression disorder is also introduced. Several key issues regarding this topic will be pointed out and discussed, including how to transfer lab-level research outcomes to real-world applications. Finally, I will show several real BCI systems developed in our lab using videos, the Neural Engineering & Smart Systems Lab (NESSLab) at National Taipei University of Technology.
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