TC Leadership
TC Co-Chair
Michael H. Smith
University of California, Berkeley, USA
TC Co-Chair
Vinod A Prasad
Nanyang Technological University, Singapore
TC Co-Chair
Seong-Whan Lee
Department of Brain and Cognitive Engineering, Korea University, Korea
TC Co-Chair
Ricardo Chavarriaga
Ecole Polytechnique Fédérale de Lausanne, Switzerland
Our Goal
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.
Members
- 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
- Ricardo Chavarriaga, Ecole Polytechnique Fédérale de Lausanne, Switzerland
- 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
- Dimitar Filev, Ford Research & Innovation Center, USA
- Jack Gallant, University of California, Berkeley, USA
- 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
- Randy Hover, SDSMT, South Dakota, USA
- Yaoping Hu, University of Calgary, Alberta, Canada
- Guang-Bin Huang, Nanyang Technological University, Singapore
- Jack J. Judy, University of Florida, USA
- Khizer Khaderi, Vizzario Inc, 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
- Seong-Whan Lee, Department of Brain and Cognitive Engineering, Korea
- Robert Leeb, Center for Neuroprosthetics, EPFL, Switzerland
- Joel Libove, Furaxa Inc., USA
- 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
- Chang Soo (CS) Nam, North Carolina State 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
- Vinod A Prasad, Nanyang Technological University, Singapore
- 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
- Michael H. Smith, University of California, Berkeley, USA
- Adrian Stoica, Jet Propulsion Laboratory, USA
- Kavitha P. Thomas, Nanyang Technological University, Singapore
- Ljiljana Trajkovic, Simon Fraser University, Canada
- Pete Trautman, Galois, Inc., USA
- Juan P. Wachs, Purdue University, USA
- Dongrui Wu, Machine Learning Lab, GE Global Research, USA
- Dingguo Zhang, Institute of Robotics, Shanghai Jiao Tong University, China
BMI Workshop Webinars
Presentations recorded during the BMI Workshop webinars at IEEE SMC 2016.
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
Learn More
These materials provide more information on topics of interest to our technical committee.
- Article featured on cover page of SMC Magzine October 2016: “Interface Marriage: A Brain-Computer Interface for Decoding Arm Movement Kinematics and Motor Control”
- 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)
Recent Activities
- 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.
Join Us
- 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.