Brain-Machine Interface Systems
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.
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
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)
- 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.