Control of a commercially available vehicle by a tetraplegic human using a brain-computer interface
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| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2025
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| author | Zou, Xinyun Gamez, Jorge Menon, Meghna Ring, Phillip Boulay, Chadwick Chitneni, Likhith Brennecke, Jackson Melby, Shana R. Kureel, Gracy Pejsa, Kelsie Rosario, Emily R. Bari, Ausaf A. Ravindran, Aniruddh Aflalo, Tyson Kellis, Spencer S. Filev, Dimitar Solzbacher, Florian Andersen, Richard A. |
| author_facet | Zou, Xinyun Gamez, Jorge Menon, Meghna Ring, Phillip Boulay, Chadwick Chitneni, Likhith Brennecke, Jackson Melby, Shana R. Kureel, Gracy Pejsa, Kelsie Rosario, Emily R. Bari, Ausaf A. Ravindran, Aniruddh Aflalo, Tyson Kellis, Spencer S. Filev, Dimitar Solzbacher, Florian Andersen, Richard A. |
| contents | 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 proof-of-concept that takes into account the safety and feasibility of BCI-controlled driving. The final BCI system added click control for full-stop braking and thus enabled bimanual cursor-and-click control for simulated town driving with the same proficiency level as the motor intact control group through a virtual town with traffic. This first-of-its-kind implantable BCI application not only highlights the versatility and innovative potentials of BCIs but also illuminates the promising future for the development of life-changing solutions to improve independent mobility for those who suffer catastrophic neurological injury. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_11805 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Control of a commercially available vehicle by a tetraplegic human using a brain-computer interface Zou, Xinyun Gamez, Jorge Menon, Meghna Ring, Phillip Boulay, Chadwick Chitneni, Likhith Brennecke, Jackson Melby, Shana R. Kureel, Gracy Pejsa, Kelsie Rosario, Emily R. Bari, Ausaf A. Ravindran, Aniruddh Aflalo, Tyson Kellis, Spencer S. Filev, Dimitar Solzbacher, Florian Andersen, Richard A. Systems and Control Neural and Evolutionary Computing Robotics 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 proof-of-concept that takes into account the safety and feasibility of BCI-controlled driving. The final BCI system added click control for full-stop braking and thus enabled bimanual cursor-and-click control for simulated town driving with the same proficiency level as the motor intact control group through a virtual town with traffic. This first-of-its-kind implantable BCI application not only highlights the versatility and innovative potentials of BCIs but also illuminates the promising future for the development of life-changing solutions to improve independent mobility for those who suffer catastrophic neurological injury. |
| title | Control of a commercially available vehicle by a tetraplegic human using a brain-computer interface |
| topic | Systems and Control Neural and Evolutionary Computing Robotics |
| url | https://arxiv.org/abs/2508.11805 |