Stroke patients could walk again with help from brain-computer interface
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Researchers at the University of Houston, Texas, USA, have demonstrated that a non-invasive brain-computer interface could help stroke patients re-learn to walk.
Studying electroencephalogram (EEG) records can tell a researcher or clinician a lot about its subject, including whether they were standing or walking at the time it was taken. It was not known, however, whether the act of standing or walking could be aided with the use of a similar brain-computer interface.
Believing that such an aid could have potential applications in rehabilitation, researchers at the University of Houston’s Non-invasive Brain-Machine Interface System Laboratory began to use standard brain monitoring techniques to identify which regions of the brain are involved in certain actions, such as walking.
Such information can be used to develop an algorithm or brain-machine interface capable of reading a subject’s intentions, and translating these into actions.
Next, the team of engineers collected data from a group of people as they walked on a treadmill, watching an avatar walking in perfect sync with them. The people wore a 64-channel headset, and motion sensors were attached at various points down their legs.
While in early tests, the avatar on the screen was controlled entirely by the motion sensors, in later tests, the avatar was controlled by the brain-computer interface. This meant that the subjects were able to control the avatar entirely with their own mind.
While the interface did not allow for perfectly coordinated movement, as the people learned to use the interface, their performance improved.
“It’s like learning to use a new tool or sport,” said Professor Jose Luis Contreras-Vidal, professor of electrical and computer engineering at the University of Houston. “You have to understand how the tool works. The brain needs time to learn that.”
The researchers, writing in Scientific Reports, suggest that this technology could assist in the rehabilitation of patients suffering gait disabilities after strokes and spinal cord injuries, by enhancing the involvement of the brain during walking.
While similar work has been done in primates, this is the first time such technology has been shown to work for humans.
“The appeal of brain-machine interface is that it places the user at the centre of the therapy,” said Professor Contreras-Vidal. “They have to be engaged, because they are in control.”