[Tutorial 6] How to Improve Performance in Brain-Computer/Machine Interface

Date & Time:

Sunday, October 7, 15:20 – 17:20

Location:

2F R03 (Gibraltar)

Speaker:

Sung Chan Jun, Minkyu Ahn

Abstract:

A brain-computer/machine interface (BCI/BMI) is an emerging direct communication pathway between a brain and external devices. Over the past several decades, BCI/BMI technology has improved greatly in speed and accuracy, and its control paradigms have diversified. Considering the number of publications on BCI/BMI, interest in BCI/BMI research has increased dramatically and has led to the improvement of BCI/BMI systems. In this tutorial, BCI/BMI techniques are introduced; basic components of BCI/BMI, popular control paradigms and underlying methodological approaches are reviewed in a brief manner. Then the following current hot issues in BCI/BMI are mainly discussed in a detailed manner:

  • Performance variation and illiteracy of BCI/BMI
  • Correlates of performance and prescreening approaches
  • Zero-training approaches
  • Achieving the reliable BCI system

Lastly, future outlook as well as R&D trends of BCI/BMI are discussed.

Short Biography:

Sung Chan Jun majored in Mathematics and minored in Computer Science from Korea Advanced Institute of Science and Technology (KAIST), South Korea. He received M.S. and PhDin Applied Mathematics at the same institution in 1993 and 1998, respectively. He coordinated software development for Korean MEG system and worked at the Department of Computer Science, University of New Mexico, USA. Then he moved to the Biological & Quantum Physics Group, Los Alamos National Laboratory, USA. He is currently working at the Gwangju Institute of Science and Technology (GIST), Korea as full professor. His current research interests are biomedical imaging and biosignal processing with MEG/EEG, braincomputer/ machine interface, computational modeling of electrical brain stimulation, and so on. He is a member of the IEEE, the Society for Neuroscience, APSIPA, and OHBM. Currently, he is Chair of Technical Committee (APSIPA BioSiPS). He serves as an active editorial board members of Brain-Computer Interfaces (published by Taylor & Francis), Frontiers in Human Neuroscience, Frontiers in Neuroscience, and Frontiers in Neuroinformatics.

Minkyu Ahn majored in Computer Engineering from Chungbuk National University, South Korea. He studied Brain Engineering and received his M.S. and PhD at Gwangju Institute of Science and Technology in 2010 and 2014, respectively. He worked as a postdoctoral researcher at the department of Neuroscience, Brown University and the department of Neurosurgery, Rhode Island Hospital, Providence, U.S. After that period, he moved to Handong Global University, South Korea in 2017, and is currently working as an assistant professor. His primary research areas are Brain-Computer Interface, Digital healthcare and Deep Brain Stimulation. He served as a Treasurer of the IEEE Providence Section EMBS Chapter in 2015-2016, and currently a member of IEEE, IEEE Engineering in Medicine and Biology Society, the BCI society and The Korean Society of Medical & Biological Engineering. He is also an active reviewer in the journals (Journal of Neural Engineering, Biomedical Engineering Letters, Neuroscience Letters, Frontiers in Human Neuroscience, and so on.)