Special Session on Affective Brain-Computer Interaction

Over the last decade, there has been a rising tendency in affective Brain-Computer Interaction (aBCI) research to enhance Brain-Computer Interaction systems with the ability to detect, process, and respond to users emotional states. Besides logical intelligence, the introduction of emotional intelligence into BCI to create aBCI has received increasing interest from interdisciplinary research fields including psychology, neuroscience, computer science, and computational intelligence. In this new domain of affective sciences, aBCI aims to narrow the communication gap between the highly emotional human and the BCI systems by developing computational systems that recognize and respond to human emotions. Various applications of aBCI systems have been proposed such as workload monitoring, driving fatigue detection, implicit affective tagging, and game adaptation.

With the fast development of embedded systems and wearable technology, it is now conceivable to port aBCI systems from laboratory to real-world environments. Various advanced dry electrodes and embedded systems including some commercial products are developed to handle the wearability, portability, and practical use of these systems in real world applications. aBCI includes affective sensing, emotion detection and feedback from brain signals and other physiological activity, which extends the concept of conventional BCI.

Although significant advances have been made and many applications have been proposed, the problem of detecting, modeling and regulating emotions in aBCI systems remains complex and largely unexplored. There exist many critical challenges in aBCI systems. How can we deal with artifacts and noises in uncontrolled real-world environments? How can machines respond to the recognized affective states and bring users to a desired affective state? How can we elicit and measure emotions in social setting? How can we develop adaptive aBCI systems that address individual differences and changing environments? How can we introduce contextual information to aBCI? What are the neural patterns or signatures for different emotional states and how is the stability of computational models over time? The goal of this special session is to connect researchers from related fields to discuss the state-of-the-art progress and enhance inter-disciplinary collaborations in aBCI. We are soliciting original contributions for addressing the above research questions.

Topics of interest:

The topics of interest include, but not limited to:

  • Emotional intelligent theory,methods and technology for aBCI
  • Multimodal deep learning for aBCI through combining neurophysiological and peripheral physiological signals
  • Thansfer learning for improving performance of aBCI
  • Feature extraction and selection methods for aBCI
  • Evaluation methods for aBCI
  • Wearable technology for aBCI
  • Affective sensing using neurophysiological signals
  • Affective neural-feedback and regulation
  • Emotion elicitation and database development
  • Applications of aBCI to social interactions
  • aBCI for neural rehabilitation such as motor function
  • aBCI for diagnosis of mental diseases such as ADHD and autism

Paper Submission:

Potential authors must submit their manuscripts through the WCCI2016 paper submission system. All the submissions will go through peer review. Details on manuscript submission can be found from http://www.wcci2016.org/submission.php. Accepted papers will be published by IEEE as part of the proceedings of WCCI2016

Important Dates:

Paper Submission deadline: January 31st, 2016
Notification of acceptance of papers: March 15, 2016
Final Paper submission and early registration deadline:April 15, 2016


Bao-Liang Lu, Shanghai Jiao Tong University, bllu@sjtu.edu.cn

Thierry Pun, University of Geneva, Thierry.Pun@unige.ch

Milos R. Popovic, University of Toronto, milos.popovic@utoronto.ca

Hiroshi Yokoi, The University of Electro-Communications, yokoi@mce.uec.ac.jp

Program Committee:

Hussein Abbass, University of New South Wales – Canberra, H.Abbass@adfa.edu.au

Cesar Marquez Chin, Toronto Rehabilitation Institute, Cesar.Marquez@uhn.ca

Guillaume Chanel, Swiss Center for Affective Sciences, Univ. of Geneva, Switzerland, guillaume.chanel@unige.ch

Sejdic Ervin, University of Pittsburgh, esejdic@pitt.edu

Cuntai Guan, The Institute for Infocomm Research, A*STAR, ctguan@i2r.a-star.edu.sg

Theodoros Kostoulas, CS Dpt. & Swiss Center for Affective Sciences, Univ. of Geneva, Switzerland, theodoros.kostoulas@unige.ch

Yuanqing Li, South China University of Technology, auyqli@scut.edu.cn

Chin-Teng Lin, National Chiao-Tung University, ctlin@mail.nctu.edu.tw

Jingquan Liu, Shanghai Jiao Tong University, jqliu@sjtu.edu.cn

Fabien Lotte, INRIA Bordeaux Sud-Ouest, France, fabien.lotte@inria.fr

Gary Garcia Molina, Philips Research North America & Univ. Wisconsin-Madison, USA, gary.garcia@philips.com

Christian Mühl, German Aerospace Center, Cologne, Germany, cmuehl@gmail.com

Maki Sakamoto, The University of Electro-Communications, sakamoto@inf.uec.ac.jp

Aureli Soria-Frisch, Starlab Barcelona SLU, Spain, aureli.soria-frisch@starlab.es

José Zariffa, University of Toronto, jose.zariffa@utoronto.ca

Center for Brain-like Computing and Machine Intelligence