There is a big push in brain science to understand what exercise does in terms of motor learning or motor retraining of the human brain.
"Brain cap" technology being developed at the University of Maryland allows users to turn their thoughts into motion. Associate Professor of Kinesiology José 'Pepe' L. Contreras-Vidal and his team have created a non-invasive, sensor-lined cap with neural interface software that soon could be used to control computers, robotic prosthetic limbs, motorized wheelchairs and even digital avatars.
"We are on track to develop, test and make available to the public—within the next few years—a safe, reliable, noninvasive brain computer interface that can bring life-changing technology to millions of people whose ability to move has been diminished due to paralysis, stroke or other injury or illness," said Contreras-Vidal of the university's School of Public Health.
The potential and rapid progression of the UMD brain cap technology can be seen in a host of recent developments, including a just published study in the "Journal of Neurophysiology," new grants from the National Science Foundation (NSF) and National Institutes of Health (NIH), and a growing list of partners that includes the University of Maryland School of Medicine, the Veterans Affairs Maryland Health Care System, the Johns Hopkins University Applied Physics Laboratory, Rice University and Walter Reed Army Medical Center's Integrated Department of Orthopaedics & Rehabilitation.
"We are doing something that few previously thought was possible," said Contreras-Vidal, who is also an affiliate professor in Maryland's Fischell Department of Bioengineering and the university's Neuroscience and Cognitive Science Program. "We use EEG (electroencephalography) to non-invasively read brain waves and translate them into movement commands for computers and other devices.
Contreras-Vidal and his team have published three major papers on their technology over the past 18 months, the latest a just released study in the "Journal of Neurophysiology" in which they successfully used EEG brain signals to reconstruct the complex 3-D movements of the ankle, knee and hip joints during human treadmill walking. In two earlier studies they showed (1) similar results for 3-D hand movement and (2) that subjects wearing the brain cap could control a computer cursor with their thoughts.
Alessandro Presacco, a second-year doctoral student in Contreras-Vidal's Neural Engineering and Smart Prosthetics Lab, Contreras-Vidal and co-authors write that their "Journal of Neurophysiology" study indicated "that EEG signals can be used to study the cortical dynamics of walking and to develop brain-machine interfaces aimed at restoring human gait function."
Contreras-Vidal and his team are collaborating on a rapidly growing cadre of projects with researchers at other institutions to develop thought-controlled robotic prosthetics that can assist victims of injury and stroke.
Their latest partnership is supported by a new $1.2 million NSF grant. Under this grant, Contreras-Vidal's Maryland team is embarking on a four-year project with researchers at Rice University, the University of Michigan and Drexel University to design a prosthetic arm that amputees can control directly with their brains, and which will allow users to feel what their robotic arm touches.
"There's nothing fictional about this," said Rice University co-principal investigator Marcia O'Malley, an associate professor of mechanical engineering. "The investigators on this grant have already demonstrated that much of this is possible. What remains is to bring all of it -- non-invasive neural decoding, direct brain control and (touch) sensory feedback -- together into one device."
In a NIH-supported project now underway, Contreras-Vidal and his colleagues are pairing their brain cap's EEG-based technology with a DARPA-funded next-generation robotic arm designed by researchers at the Johns Hopkins Applied Physics Laboratory to function like a normal limb. And the UMD team is developing a new collaboration with the New Zealand's start-up Rexbionics, the developer of a powered lower-limb exoskeleton called Rex that could be used to restore gait after spinal cord injury.
"There is a big push in brain science to understand what exercise does in terms of motor learning or motor retraining of the human brain," says Larry Forrester, an associate professor of physical therapy and rehabilitation science at the University of Maryland School of Medicine.
For more than a year, Forrester and the UMD team have tracked the neural activity of people on a treadmill doing precise tasks like stepping over dotted lines. The researchers are matching specific brain activity recorded in real time with exact lower-limb movements. They just received a new NIH grant of almost 1 million dollars to support this work, which was originally funded by a small "seed" grant from the University of Maryland, College Park and the University of Maryland, Baltimore.
During the past two decades a great deal of progress has been made in the study of direct brain to computer interfaces, most of it through studies using monkeys with electrodes implanted in their brains. However, for use in humans such an invasive approach poses many problems, not the least of which is that most people don't' want holes in their heads and wires attached to their brains.
A paper Contreras-Vidal and colleagues published in the "Journal of Neuroscience" in March 2010 showed the feasibility of Maryland's EEG-based technology to infer multidimensional natural movement from noninvasive measurements of brain activity. In their two latest studies, Contreras-Vidal and his team have further advanced the development of their EEG brain interface technology, and provided powerful new evidence that it can yield brain computer interface results as good as or better than those from invasive studies, while also requiring minimal training to use.
In a paper published in April in the "Journal of Neural Engineering," the Maryland team demonstrated that people wearing the EEG brain cap, could after minimal training control a computer cursor with their thoughts and achieve performance levels comparable to those by subjects using invasive implanted electrode brain computer interface systems. Contreras-Vidal and his co-authors write that this study also shows that compared to studies of other noninvasive brain control interface systems, training time with their system was substantially shorter, requiring only a single 40-minute session.