EPFL and Nissan researchers are able to read a driver's brain signals and send them to a smart vehicle so that it can anticipate the driver's moves and facilitate the driving process. Nissan recently unveiled this brain-to-vehicle (B2V) technology. Future cars will be both self-driving and manual. "We wanted to harness technology to enhance drivers' skills without interfering with the enjoyment of being behind the wheel," explains José del R. Millán, who holds the Defitech Foundation Chair in Brain-Machine Interface (CNBI). As part of a joint project with Nissan researchers based at the CNBI, the team managed to read the brain signals that indicate a driver is about to do something – such as accelerate, brake or change lanes – in order to send that information to the vehicle.
A woman who is completely paralyzed below the neck has regained the ability to reach out and interact with the world around her thanks to the most advanced brain-computer interface for operating a robotic arm so far. Each chip has 96 electrodes and is wired through the skull to a computer that translates her thoughts into signals for the robotic arm. The work, performed by researchers from the University of Pittsburgh, is reported in the latest issue of The Lancet. The work is the latest advance to show how brain-controlled interface technology can restore some movement to quadriplegics. In May of this year, researchers at Brown University described how a paralyzed patient could use a robotic limb to perform basic tasks, including giving herself a drink of coffee (see "Brain Chip Helps Quadriplegics Move Robotic Arms with Their Thoughts").
Scientists at Duke University have demonstrated a wireless brain-machine interface (BMI) that allows monkeys to navigate a robotic wheelchair using their thoughts. This is the first long-term wireless BMI implant that has given high-quality signals to precisely control a wheelchair's movements in real time. "This is the first wireless brain-machine interface for whole-body locomotion," says Miguel Nicolelis, professor of neuroscience at Duke who led the work published in the journal Scientific Reports. "Even severely disabled patients who cannot move any part of their body could be placed on a wheelchair and be able to use this device for mobility." Nicolelis and his colleagues pioneered brain-machine interfaces in a 1999 study on rats.
Elon Musk announced late Tuesday night that the final goal of Neuralink, his brain-machine interface startup, is to allow humans to "achieve a symbiosis with artificial intelligence," and that by "merging with AI," humans will be able to keep up with AI. Musk plans to begin human trials on an early version of Neuralink intended to treat brain injuries next year. "Ultimately we can do a full brain machine interface," Musk said in an announcement that was widely livestreamed. "This is going to sound pretty weird. Ultimately we can achieve a symbiosis with artificial intelligence. This is not a mandatory thing, this is something you can choose to have if you want. This is going to be really important at a civilization-level scale. Even in a benign AI scenario, we will be left behind. With a high-bandwidth brain machine interface we can go along for the ride and have the option of merging with AI." Musk has become famous for his moonshot projects, his lofty promises, his quick temper on Twitter, and his various plans for society that don't include input from the rest of us.
The culmination of work by Alistair C. McConnell (lead-researcher) through his PhD and the SOPHIA team, the Soft Orthotic Physiotherapy Hand Interactive Aid (SOPHIA) forms the foundation for our future research into Soft Robotic rehabilitation systems. Through Alistair's research, it became apparent that there was a lack of stroke rehabilitation systems for the hand, that could be used in a domestic environment and monitor both physical and neural progress. Alistair conducted a thorough review of the literature to fully explore the state of the art, and apparent lack of this type of rehabilitation system. This review investigated the development of both Exoskeleton and End-Effector based systems to examine how this point was reached and what gaps and issues still occurred. From this review and discussions with physiotherapists, we developed an idea for a brain machine controlled soft robotic system.