Control of a commercially available vehicle by a tetraplegic human using a brain-computer interface
Xinyun Zou, Jorge Gamez, Meghna Menon, Phillip Ring, Chadwick Boulay, Likhith Chitneni, Jackson Brennecke, Shana R. Melby, Gracy Kureel, Kelsie Pejsa, Emily R. Rosario, Ausaf A. Bari, Aniruddh Ravindran, Tyson Aflalo, Spencer S. Kellis, Dimitar Filev, Florian Solzbacher

TL;DR
This study demonstrates a brain-computer interface enabling a tetraplegic individual to remotely control a vehicle in real-world and simulated environments, showcasing potential for mobility restoration.
Contribution
First real-world implementation of a BCI-controlled vehicle allowing a tetraplegic person to drive remotely using intracortical signals.
Findings
Participant with tetraplegia reacted as fast as able-bodied controls.
Successfully drove a Ford Mustang remotely in real-world conditions.
Achieved full control including braking and steering in simulated driving tasks.
Abstract
Brain-computer interfaces (BCIs) read neural signals directly from the brain to infer motor planning and execution. However, the implementation of this technology has been largely limited to laboratory settings, with few real-world applications. We developed a BCI system to drive a vehicle in both simulated and real-world environments. We demonstrate that an individual with tetraplegia, implanted with intracortical BCI electrodes in the posterior parietal cortex (PPC) and the hand knob region of the motor cortex (MC), reacts at least as fast and precisely as motor intact participants. This BCI participant, living in California, could also remotely drive a Ford Mustang Mach-E vehicle in Michigan. Our teledriving tasks relied on cursor movement control for speed and steering in a closed urban test facility and through a predefined obstacle course. These two tasks serve as a…
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