Paralyzed Man Moves Robotic Arm with Thoughts
Researchers at UC San Francisco have enabled a paralyzed man to control a robotic arm using a brain-computer interface (BCI) that translates his imagined movements into real actions. The AI-powered device functioned for a record seven months without needing recalibration, unlike previous BCIs that lasted only a few days. The key innovation was training the AI to adapt to small shifts in brain activity over time, allowing for continuous use.
The study participant, who had been paralyzed by a stroke, had sensors implanted on his brain that recorded movement-related signals when he imagined moving. After weeks of training with a virtual robotic arm, he successfully controlled a real robotic arm, performing tasks like picking up objects and using a water dispenser. Even months later, he retained control with only minor adjustments.
The research, published in Cell and funded by the National Institutes of Health, marks a significant step toward practical BCIs for people with paralysis. Researchers are now refining the technology to improve movement speed and plan to test it in home settings, potentially transforming daily life for individuals with disabilities.