
This is not a video game fantasy, but a real program that engineers at The University of Texas at Austin have created as part of research into brain-computer interfaces to help improve the lives of people with motor disabilities. More importantly, the researchers incorporated machine learning capabilities with their brain-computer interface, making it a one-size-fits-all solution.
Imagine playing a racing game like Mario Kart, using only your brain to execute the complex series of turns in a lap.
Typically, these devices require extensive calibration for each user — every brain is different, both for healthy and disabled users — and that has been a major hurdle to mainstream adoption. This new solution can quickly understand the needs of an individual subject and self-calibrate through repetition. That means multiple patients could use the device without needing to tune it to the individual.
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