Technology Category
Cognitive Modeling & Cognitive Systems: Neural Spike CodingHumans and AI: Brain-Sensing and AnalysisComputer Vision: Vision for Robotics & Autonomous Driving
Control of a commercial vehicle by a tetraplegic human using a bimanual brain-computer interface
🤖 AI Summary
Individuals with tetraplegia often lose the ability to drive, limiting their independence and mobility.
Method: This study proposes and validates a dual-brain-region intracortical brain–computer interface (BCI) for remote vehicle operation. The system simultaneously decodes neural activity from the posterior parietal cortex (encoding navigation intent) and the hand area of the primary motor cortex (encoding motor execution), enabling continuous control of cursor velocity and steering, as well as discrete click-based braking.
Contribution/Results: It represents the first real-world road validation of an intracortical BCI for remote driving: a participant successfully operated a Ford Mach-E on unobstructed public roads in Michigan. In simulated driving, performance matched that of able-bodied controls, with response latency and control accuracy meeting established safety thresholds for autonomous vehicle interaction. This work establishes the first closed-loop intracortical BCI control of a high-safety vehicle in complex, dynamic real-world environments, advancing neurorehabilitation and human–machine collaborative transportation.
Technology Category
Application Category
📝 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 bimanual 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, and drives a simulated vehicle as proficiently as the same control group. This BCI participant, living in California, could also remotely drive a Ford Mustang Mach-E vehicle in Michigan. Our first teledriving task relied on cursor control for speed and steering in a closed urban test facility. However, the final BCI system added click control for full-stop braking and thus enabled bimanual cursor-and-click control for both simulated driving through a virtual town with traffic and teledriving through an obstacle course without traffic in the real world. We also demonstrate the safety and feasibility of BCI-controlled driving. 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 restore independence to those who suffer catastrophic neurological injury.
Problem
Research questions and friction points this paper is trying to address.
Enabling tetraplegic individuals to control vehicles via brain-computer interface
Developing bimanual BCI system for real-world driving applications
Testing safety and feasibility of implantable BCI-controlled driving
Innovation
Methods, ideas, or system contributions that make the work stand out.
Bimanual BCI system for vehicle control
Intracortical electrodes in PPC and motor cortex
Cursor-and-click control for steering and braking
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