Paralyzed Man Pilots Virtual Drone Using Brain Implant


Paralyzed Man Pilots Virtual Drone Using Brain Implant

TEHRAN (Tasnim) – A breakthrough brain-computer interface (BCI) has enabled a 69-year-old man with tetraplegia to control a virtual drone through an obstacle course, solely by imagining finger movements.

Researchers from the University of Michigan have developed an innovative algorithm that converts neural signals into precise controls, offering new potential for individuals with severe paralysis.

The participant, whose paralysis was caused by a spinal cord injury, used an implanted device made by Blackrock Neurotech. This BCI system, consisting of 192 electrodes in the brain's hand-motion control area, interpreted his imagined finger and thumb movements.

The system relied on an AI model that mapped these complex brain signals into four distinct inputs. By imagining motions of specific finger groups, the participant generated varying electrical signals. These allowed him to skillfully pilot a simulated drone, maneuvering it through a challenging obstacle course.

“The goal of doing the quadcopter was really kind of shared between our lab and the participant,” said Matthew Willsey, a researcher involved in the study. “For him, it was the realization of a dream that he thought was lost once he suffered his injury. He had a passion and a dream for flying.”

Willsey added that the experiment could have been performed with a real drone but remained virtual for safety and convenience. The participant reportedly felt empowered by the achievement, often asking for videos of his progress to share with friends.

Despite this success, challenges persist in advancing BCI technology for broader, complex applications. AI-based systems require extensive, user-specific training to interpret signals accurately. These models also need regular retraining to maintain functionality, as electrode placement or changes in the brain over time can impact performance.

The study underscores the potential of BCIs in restoring autonomy to individuals with paralysis, though further development is needed to improve reliability and scalability.

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