Mind-Machine Interface Turns Thought into Motion

Photo: Photo of a man with a brain cap

"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 Associate Professor of Kinesiology José Pepe L. Contreras-Vidal of the university's School of Public Health.

"We use EEG [electroencephalography] to non-invasively read brain waves and translate them into movement commands for computers and other devices,” said Contreras-Vidal. There are other brain computer interface technologies under development, but Contreras-Vidal notes that these competing technologies are either very invasive, requiring electrodes to be implanted directly in the brain, or, if noninvasive, require much more training to use than does UMD's EEG-based, brain cap technology.

This data could help stroke victims in several ways, Forrester says. One is a prosthetic device, called an "anklebot," or ankle robot, that stores data from a normal human gait and assists partially paralyzed people. People who are less mobile commonly suffer from other health issues such as obesity, diabetes or cardiovascular problems, Forrester says, "so we want to get for example stroke survivors up and moving by whatever means possible."

The second use of the EEG data in stroke victims is more complex, yet offers exciting possibilities. "By decoding the motion of a normal gait," Contreras-Vidal says, "we can then try and teach stroke victims to think in certain ways and match their own EEG signals with the normal signals." This could "retrain" healthy areas of the brain in what is known as neuroplasticity.

"EEG monitoring of the brain, which has a long, safe history for other applications, has been largely ignored by those working on brain-machine interfaces, because it was thought that the human skull blocked too much of the detailed information on brain activity needed to read thoughts about movement and turn those readings into movement commands for multi-functional high-degree of freedom prosthetics," said Contreras-Vidal. He is among the few who have used EEG, MEG or other sensing technologies to develop non-invasive neural interfaces, and the only one to have demonstrated decoding results comparable to those achieved by researchers using implanted electrodes.


COMPAMED.de; Source: The University of Maryland