Please click here to download an electronic version of the BMI booklet.

Panels

• Merging minds and machines: Using BMI to meld human minds with AI; Science fiction or inevitable future?
  Friday, October 6, 8:00-9:30 AM MB252
  Moderator: Jack Gallant (UC Berkeley, USA). Panelists: Randy Goebel (Univ. Alberta); Yingxu Wang (Univ. Calgary); Ricardo Chavarriaga (EPFL); Jianbo Lu (Ford Research)

Recent advances in AI have spurred efforts to develop a new generation of more powerful invasive or noninvasive BMIs that would enable seamless brain-to-machine communication. This panel will discuss all aspects of these efforts, including: What are the obstacles to creating a seamless interface between mind and machine? Can AI improve the performance of BMIs? Can BMIs improve the performance of AI? How can AI be used to improve the performance of BMIs? What will emerge out of the melding of mind and machine? What privacy concerns should we be aware of and how should we address them? Are there other risks of merging mind and machine?

• Important topics in designing and building real world BMI systems: What is new?
  Saturday, October 7, 1:20-2:10 PM MB252
  Moderator: Jack Gallant (UC Berkeley, USA). Panelists: Tiago Falk (INRS-EMT); Conor Russomanno (OpenBCI); Tom Ladd (Smartstones); Tim Mullen, (Qusp); Irene Mikawoz (Natural Sciences and Engineering Research Council of Canada)

The goal of the Brain-Machine Interface (BMI) panel is to hear about the current challenges and hot topics in BMI research from experts on the funding, design, and use of Brain-Machine Interface/Brain-Computer Interface (BMI/BCI) systems. By identifying the challenges confronting the successful clinical translation and commercial application of BMI/BCI systems in real-world situations, this panel should identify some opportunities for Systems, Man, and Cybernetics and other efforts to dramatically improve BMI/BCI system performance and benefits for the patients and/or users.

Tutorials - October 5th 2017

• Designing brain-computer interfaces for users with motor and cognitive disabilities.
  Organizers: R. Chavarriaga (EPFL, Switzerland), M. Grosse-Wentrup, M. Hohmann (MPI Tuebingen, Germany)
  October 5th 2017 8h30-11h30

One of the main motivations for BCI is to provide assistive technologies for users with sever motor disabilities. Nevertheless, most studies are currently performed with control subjects and their results translate poorly to the target population. Critically, the field lacks knowledge and methods to solve this issue. This tutorial will present state-of-the-art research oriented to advance this field and contribute to overcome this roadblock. Given the characteristics of the intended users, designing reliable systems requires careful evaluation of their requirements and capacities. Proper combination of machine learning techniques, methods for human-machine interaction and adaptive processes are necessary to adequately suit the developed systems. This tutorial will provide SMC attendees –both novice and with previous BMI expertise- with important tools to deploy and test their systems outside the research laboratories and get them closer to practical applications.

• Brain-Machine Interface Systems - Overview, Applications and Research Challenges.
  Organizer: N. Robinson, K. Thomas (NTU, Singapore)
  October 5th 2017 13h30 - 17h00

Brain-Machine Interfaces are systems that translate the user's intention coded by brain activity measures into a control signal without using activity of any muscles or peripheral nerves. These control signals can potentially be employed to substitute motor capabilities (e.g. brain-controlled prosthetics for amputees or patients with spinal cord injuries, brain-controlled wheel chair); to help in the restoration of such functions (e.g. as a tool for stroke rehabilitation), to enable alternative communication (e.g. virtual keyboard, speller etc.) for those who are disabled or otherwise unable to communicate, and other applications such as serious games for enhancing cognition skills. This tutorial will provide an overview of Brain-Machine Interface (BMI), real-world applications, methods for brain signal acquisition and their comparison, relevant Electroencephalogram (EEG) signal features for BMI and signal processing & machine learning tools for BMI. Further, the talk will cover research challenges and developments in this BMI. Further, some selected non-invasive BMI research work from our group on decoding arm movement kinematics and motor control as well as biometric identification will also be presented. The tutorial will conclude highlighting potential future BMI research topics.