Technical Program >
Featured BMI Workshop
3rd Annual Workshop on Brain-Machine Interfaces
October 10-11, 2011
BMI Workshop Co-Chairs
José del R. Millán, IEEE SMCS;
Michael H. Smith, IEEE SMCS;
Mohamad Sawan, IEEE CASS; Jose Carmena, IEEE EMBS
Brain-Machine Interface (BMI) systems offer the possibility of a new generation
of technologies that allow users to directly control various devices directly
via the nervous system. This Workshop on Brain-Machine Interfaces,
co-sponsored jointly by the IEEE Systems, Man, and Cybernetics Society (SMC),
Circuits and Systems Society (CAS), and the Engineering, Medicine and Biology Society (EMBS),
provides an international forum for researchers and practitioners to report
the latest innovations, summarize the state-of-the-art, and exchange ideas
and advances in all aspects of BMI.
This year's theme is
Problems and Solutions in Building Real-World BMI Systems, and is adopted with acknowledgment that
wxperts from many research areas within SMC, CAS, and EMBS as well as outside ones are needed if working real-world
BMI systems are ever to be built. Advances in IEEE SMC's, CAS's and EMBS's fields of interest as they relate to BMI
are expected to enable the building of future Brain-Machine Interface Systems capable of operating in the real-world
with real people. This workshop will be of special interest to those experts in the technical areas covered by
SMC, CAS, EMBS, and other IEEE and non-IEEE related areas who are interested in learning how their research areas
can be applied to the solving of various research problems necessary for the development of real-world BMI systems.
Besides presentations of accepted papers, this 2 day workshop will feature panels,
a keynote, discussions with the audience, and prominent
invited speakers from industry and academia, listed below followed by their topics and abstracts.
Click here to download an electronic version of the original BMI Workshop CFP.
Invited Workshop Speakers
University of California, Berkeley
University of Miami
|Jose L. Contreras-Vidal
University of Maryland
Polytechnique University of Montreal
Johns Hopkins University
Case Western Reserve University
Problems and Solutions in Developing Noninvasive BMI to Powered Power-limb Exoskeleton Systems
for Restoration and Rehabilitation of Gait
Jose L. Contreras-Vidal, Ph.D.
University of Maryland, USA
Breakthroughs in the non-invasive decoding of real/visual/imagined movement and movement intent from scalp electroencephalography (EEG) now enable accurate prediction of upper extremity movement and gait in humans to reliably drive a BMI. The EEG time-domain decoders enable subjects to accomplish closed-loop brain to computer interface control in a single session, making noninvasive BMI systems to control multi-functional prosthetics/orthotics clinically feasible. In this talk I will outline the engineering, clinical, and time-permitting, regulatory problems and solutions that we need to overcome to develop a reliable EEG-based BMI system to powered lower-limb exoskeletons for clinical use in patients with spinal cord injury and stroke.
Implantable Brain-Machine Wireless Interfaces for Biosensing and Treatment of Neural Dysfunctions
Mohamad Sawan, Ph.D.
Polytechnique University of Montreal, Canada
Brain-Machine Interfaces, dedicated for biosensing and subsequent treatment of cortical neural dysfunctions, are promising alternative for monitoring and studying brain activities underlying cognitive functions and pathologies. This talk covers circuits and systems techniques used for the implementation and integration of biomedical devices. In particular, primary visual cortex stimulation and epileptic seizures detection will be described. Also treatment through microelectrostimulation and drug delivery techniques will be summarized. Global view of typical devices altogether with corresponding multidimensional design and implementation challenges such power management and high-data rate communication modules will be explained.
A Miniaturized System for Spike-Triggered Intracortical Microstimulation
in a Brain-Machine-Brain Interface
Pedram Mohseni, Ph.D.
Case Western Reserve University, Cleveland, USA
To date, brain-machine interfaces (BMIs) have sought to interface the brain with the external world using intrinsic neuronal signals as input commands for controlling external devices, or device-generated electrical signals to mimic sensory inputs to the nervous system. A new generation of neuroprostheses is now emerging that aims to combine neural recording, signal processing, and microstimulation functionalities for closed-loop operation. These devices might use information extracted from the brain neural activity to trigger microstimulation or modulate stimulus parameters in real time, potentially enhancing the clinical efficacy of neuromodulation in alleviating pathologic symptoms or restoring lost sensory and motor functions in the disabled. This talk will report on a miniaturized system for spike-triggered intracortical microstimulation as a novel, device-based approach for improving functional recovery after traumatic brain injury (TBI). The neurophysiological rationale behind this work and our current findings from experiments with anesthetized and ambulatory, brain-injured rats using a battery-powered, head-mounted microdevice will be presented. This work has the potential to remarkably advance the neurorehabilitation field at the level of functional neurons and networks.
Neural Adaptations to a Brain-Machine Interface
Jose Carmena, Ph.D.
University of California, Berkeley, USA
The advent of multi-electrode recordings and brain-machine interfaces (BMIs) has provided a powerful tool for the development of neuroprosthetic systems for people with sensory and motor disabilities. BMIs are powerful tools that use brain-derived signals to control artificial devices such as computer cursors and robots. By recording the electrical activity of hundreds of neurons from multiple cortical areas in subjects performing motor tasks we can study the spatio-temporal patterns of neural activity and quantify the neurophysiological changes occurring in cortical networks, both in manual and brain control modes of operation. In this talk I will present exciting results from our lab showing that the brain can consolidate prosthetic motor skill in a way that resembles that of natural motor learning. Using stable recording from ensembles of units from primary motor cortex in two macaque monkeys we demonstrate that proficient neuroprosthetic control reversibly reshapes cortical networks through local effects. This will be followed by an outline on the emerging directions the field is taking towards the development of neuroprosthetic devices for the impaired.
“Intelligent” Neuroprosthetics: System Design Strategies from Lab Bench to Patient Bedside
Justin C. Sanchez, Ph.D.
University of Miami, USA
Closed-loop neural interfaces have the great potential for treating neurological disorders and restoring communication/control in disabled individuals. The transformative aspect of closed-loop neural interfaces is that they can be designed as “intelligent tools” that have the capability to assist, evolve, and grow with the user. Unlike many other devices, neural interfaces exist in a shared space that seamlessly spans the user's internal, adaptive representation of the world and the physical environment enabling a much deeper human-device symbiosis. Recent advancements in the neuroscience and engineering of neural interfaces are providing a blueprint for neurophysiologic hardware design and methods for determining representation in multiscale signals for deriving therapeutic strategies. This talk covers recent advances in science and technology supporting the development of intelligent neural interfaces from the bench to bedside and contrasts them with “lessons learned” from the past 20 years of neural interface design.
Bypassing the Injured Spinal Cord: Toward Practical, Cortically Controlled
Functional Electrical Stimulation
Lee E. Miller, Ph.D., Christian Ethier, Emily R. Oby, & Nicholas Sachs
Northwestern University, Chicago, USA
Spinal cord injury causes a devastating loss of independence as well as a host of adverse physiological changes including loss of muscle tone and bone density, and compromised cardiovascular system. Functional Electrical Stimulation (FES) can be used to produce contraction of paralyzed muscles, and such efforts are underway to develop systems that would provide reach and grasp, bowel and bladder control, stance, and locomotion. Indirectly, FES can also significantly improve the overall health of spinal injured patients through the exercise it generates. Current approaches to the restoration of grasp function for patients with mid-cervical injuries use pre-programmed patterns of stimulation that are controlled by the patient using simple signals derived from residual movement of the proximal limb. However, this limits available hand functions as well as the range of patients for which it is suitable.
In contrast, we have developed an FES prosthesis that is controlled by signals recorded from a multi-electrode array implanted in the motor cortex. The system has allowed several monkeys to regain voluntary control of simple grasping movements despite temporary paralysis induced by peripheral nerve block. We are currently working to implement a number of improvements to the system: 1) We need to increase the number of independently controlled degrees of freedom through nerve, as well as intramuscular stimulation. 2) The controller must be readily recalibrated to accommodate lost or altered neural signals, but these changes must not interfere with parallel adaptive changes made by the user. 3) The system must be able to adapt to and generalize across a range of different dynamical and postural settings without recalibration and without access to the EMG signals from the normal monkey. If we are able to solve these problems using a monkey model in the laboratory setting, we believe that a similar brain-controlled FES prostheses might ultimately benefit even patients with high cervical injuries who lack the ability to control proximal arm movements.
Cortical Signals and Decoding Strategies for Dexterous Prosthesis
Nitish V. Thakor, Ph.D.
Johns Hopkins University, Baltimore, USA
A prosthetics revolution is underway - with quantum advancements in the design of dexterous prosthesis developed only within the past few years. With the availability of limbs with anthropomorphic designs that possess as many as 22 degrees of freedom, the challenge now is to develop control strategies for these limbs. The choices are myoelectric and neural interfaces. This presentation will review signals and decoding strategies based on myoelectric and neural signals (Electrocorticograms, local field potentials, and spikes) for control of dexterous limb movement, including individuated fingers and grasps. While myoelectric control is noninvasive, its decoding capability is limited, it is prone to electrode attachment problems, and is not intuitive. Neural control offers long term promise but the challenge is to decipher the cortical signals from population of neurons in different cortical regions. Our work shows that Electrocorticographic signals can provide low dimensional decoding of finger movements, while spikes and local field potentials provide finer and more accurate decoding of dexterous movements. This talk will present the generalized linear models and how population codes from neurons can be used to achieve high decoding accuracies. Finally, the challenge of utilizing the vast cortical resources for achieving high dimensional neural control of state of the art dexterous prostheses will be presented.