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2017 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces (IEEE CIBCI'17)


IEEE CIBCI 2017 will bring together researchers and practitioners from around the world to discuss the latest advances in the field of computational intelligence applied to brain computer interfaces (BCIs) and will enable a major forum for the presentation of recent results in theory, algorithms, systems and clinical applications. The lingering problems to be solved such as decoding accuracy, task performance, human factors, decoding algorithms, and feedback represent both challenges to the field and a tremendous opportunity for collaborative and multidisciplinary research, involving not only peers with expertise in the field of BCIs, but also expertise in systems engineering, human-machine systems, cybernetics, and/or other disciplines. The goal of the symposium is to facilitate the interaction and intellectual exchange between all researchers and developers of this technology and the latest advances, innovations, and applications.

Topics

Topics related to all aspects of brain computer interfaces (BCIs) and machine learning, such as theories, algorithms, systems, technologies and applications, particularly those based on computational intelligence, which include, but are not limited to:
  • Neural Networks for BCIs
  • Evolutionary Algorithms for BCIs
  • Fuzzy Sets for BCIs
  • BCIs for motor/cognitive rehabilitation
  • BCIs for assistance in neuro-wheelchair driving
  • Recent advances in BCI Spellers
  • Sensorimotor BCIs
  • Adaptive and self-calibrating BCI systems for independent use
  • Performance metrics and human factors for BCI training and operation
  • Software development systems for BCIs
  • Multi-modal BCIs and physiological computing

Accepted Special Sessions

(To be announced)

Symposium Co-Chairs


Jose Principe

University of Florida, USA
Email: principe@cnel.ufl.edu

Robert Kozma
University of Memphis, USA
Email: rkozma@memphis.edu


Program Committee

(To be announced)