Michael H. Smith
University of California, Berkeley, USA
Vinod A Prasad
Nanyang Technological University, Singapore
Department of Brain and Cognitive Engineering, Korea University, Korea
Ecole Polytechnique Fédérale de Lausanne, Switzerland
Brain-Machine Interfaces (BMI) are about transforming thought into action, or, conversely, sensation into perception. One example of this paradigm contends that a user can perceive sensory information and enact voluntary motor actions through a direct interface between the brain and a prosthetic device in virtually the same way that we see, hear, walk, or grab an object with our own natural limbs.
The primary objective of the BMI Systems Technical Committee is to bring together specialists from the different areas that will be required as part of any real-world BMI system: systems neuroscience, system integration, sensors, integrated circuits, machine learning, control, robotics, biology, clinical studies, neurologists, system engineers, cybernetic experts, human-machine professionals, and other computer scientists and engineers working in this interdisciplinary environment. The goal of the TC is to provide a basis for the exchange of information and resources among these diverse communities, to enable interactions between groups from these fields and to bring a systems perspective to the field of BMI.
- Kai Keng Ang, Institute for Infocomm Research, A*STAR, Singapore
- José M. Azorín, Miguel Hernandez University Elche, Spain
- Valentina Emilia Balas, Aurel Vlaicu University, Romania
- Hessam Bashir
- Ethan Blackford, Ball Aerospace, USA
- Laurent Bougrain, INRIA/LORIA, France
- Tom Carlson, University College London, UK
- Jose Carmena, University of California, Berkeley, USA
- Seungjin Choi, POSTECH, Korea
- C.L. Philip Chen, University of Macau, China
- Jose L. Contreras-Vidal, University of Houston, USA
- Suzana Dantas Daher, Federal University of Pernambuco, Brazil
- Justin R. Estepp, AFRL, USA
- Siamac Fazli, Korea University, Korea
- Kiran George, California State University, Fullerton, USA
- Smitha K. G., Nanyang Technological University, Singapore
- Jaeho Han, Korea University, Korea
- Michael Heidingsfeld, University Stuttgart, Germany
- Rumi Hiraga, Tsukuba University of Technology, Japan
- Jack J. Judy, University of Florida, USA
- Dong-Joo Kim, Korea University, Korea
- Robert T. Knight, University of California, Berkeley, USA
- Scott Koziol, Baylor University, USA
- Robert Kozma, University of Memphis, USA
- Robert Leeb, Center for Neuroprosthetics, EPFL, Switzerland
- Fabien Lotte, INRIA Bordeaux, France
- José del R. Millán, Swiss Federal Institute of Technology, Lausanne, Switzerland
- Byoung-Kyong Min, Korea University, Korea
- Javier Minguez, BitBrain Technologies, Spain
- Luis Montesano, Universidad de Zaragoza, Spain
- Jun Morimoto, ATR, Japan
- Tadahiko Murata, Kansai University, Japan
- Saeid Nahavandi, Deakin University, Australia
- Marcia O’Malley, Rice University, USA
- Mahesh R. Panicker, GE Global Research, Bangalore, India
- Shahram Payandeh, Simon Fraser University, Canada
- Witold Pedrycz, University of Alberta, Edmonton, Canada.
- Riccardo Poli, University of Essex, UK
- Girijesh Prasad, University of Ulster, UK
- Philipp Rapp, University Stuttgart, Germany
- Victor Raskin, Purdue University, USA
- Rodney Roberts, Florida State University, USA
- Neethu Robinson, Nanyang Technological University, Singapore
- Itzel Jared Rodriguez Martinez
- Adrian Stoica, Jet Propulsion Laboratory, USA
- Kavitha P. Thomas, Nanyang Technological University, Singapore
- Ljiljana Trajkovic, Simon Fraser University, Canada
- Juan P. Wachs, Purdue University, USA
- Dongrui Wu, Machine Learning Lab, GE Global Research, USA
BMI Workshop Webinars
Presentations by four experts in brain-machine interfaces were carried as webinars during the BMI Workshop at SMCS2014. Use the links below to view the recordings.
- Lofti Zadeh – The Information Principal
- Bob Knight – Challenges in Designing and Building Auditory Speech Prosthesis
- Jack Judy – Building Real World BMI Systems: Problems, Potential Solutions, and Funding
- José del R. Millán – Translating Brain-Machine Interfaces to End-Users: Lessons and Challenges
These tutorial materials provide more information on topics of interest to our technical committee.
- Adaptive Tracking of Discriminative Frequency Components in Electroencephalograms for a Robust Brain–Computer Interface (Paper, .PDF)
- BMI Control of Robotic Exoskeletons (Presentation, .PDF)
- Detection of Self-paced Reaching Movement Intention from EEG Signals (Paper, .PDF)
- Errare Machinale Est: The Use of Error-Related Potentials in Brain-Machine Interfaces (Paper, .PDF)
- Identifying Engineering, Clinical and Patient’s Metrics for Evaluating and Quantifying Performance of Brain-Machine Interface (BMI) Systems (Paper, .PDF)
- Identifying Engineering, Clinical and Patient’s Metrics for Evaluating and Quantifying Performance of Brain-Machine Interface (BMI) Systems (Presentation, .PDF)
- Robust BCI Algorithms for Motor Imagery Classification and Upper Limb Kinematics Decoding (Presentation, .PDF)
- Organized Workshops on BMI at SMC’09, SMC’10, and SMC’11. Organizing another workshop at SMC’14 in San Diego.
- Organized Tutorials, a Panel, and Keynote on BMI at various SMC and other conferences.
- Associate Editors for SMC Transactions journals.
- Interact with experts in Brain Machine Interface Systems, which is a relatively new and rapidly growing research field. Both invasive and non-invasive techniques (BCI) for interfacing the brain are included.
- Participate in interesting conferences and workshops.
- Make friends from different regions of the world.
- Exchange research ideas and possibly share research resources.