A brain-computer interface co-piloted by artificial intelligence (AI) could improve how people with paralysis complete tasks. AI copilots could help to improve user control by interpreting intent and assisting with movement.
The researcher created a non-invasive brain–computer interface system that can read brain activity through electrodes and use machine learning to improve movement control. The interface featured two AI copilots: one that helps to guide a computer cursor and another that assists with robotic arm tasks using visual input.
When testing the interface with the AI copilots, a participant with paralysis of the legs from a spinal cord injury achieved a 3.9-times-higher performance in controlling a computer cursor than without assistance from the AI copilot. Participants without paralysis experienced a 2.1-times-improved performance after the AI was engaged.
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