The development of cutting-edge graphene sensors has created an interface that allows you to precisely control your robot with just your thoughts. This development will have a positive impact not only on healthcare, but also on various other industries.
A Brain Machine Interface (BMI) allows a person to operate a device using brain waves. As a hands-free and voice-free interface, BMI has great potential for use in robotics, bionic prostheses, and self-driving cars.
A BMI typically consists of three modules: an external sensory stimulus, a sensing interface, and a unit that processes nerve signals. Of the three, the sensing interface is crucial as it detects electrical activity produced by the outermost layer of the brain, the cerebral cortex. The cerebral cortex is responsible for high-level processes, including motor functions.
However, it is the visual cortex, a part of the cerebral cortex, that receives and processes the information sent by the eyes and is key to BMI, which depends on visual stimulation. The visual cortex is located at the back of the brain, in the occipital lobe.
EEG is registered via implantable or wearable sensors such as electroencephalogram (EEG) electrodes. The problem with using his EEG electrodes and other non-invasive biosensors on the back of the head is that it is an area that is usually covered with hair.
Wet sensors rely on the use of conductive gel on the scalp and hair, which can cause the sensor to move when the individual moves. A dry sensor can be used as an alternative, but it also presents challenges. It’s less conductive than a wet sensor, and given the rounded shape of the head, it can be difficult to maintain proper contact.
Researchers at the University of Technology Sydney (UTS) have addressed these issues by developing a dry biosensor containing graphene. Graphene is a one-atom-thick layer of carbon atoms arranged in a hexagonal lattice that is 1,000 times thinner and 200 times stronger than a human hair. than steel.
Graphene is an ideal material for making dry biosensors due to its thinness and high electrical conductivity. It is also less susceptible to corrosion and perspiration, making it ideal for use on the head.
Researchers have found that combining graphene and silicon produces a more robust dry sensor. The graphene layer in their sensor is less than 1 nanometer thick.
“By using state-of-the-art graphene materials in combination with silicon, we were able to overcome the problems of corrosion, durability and skin contact resistance to develop a wearable dry sensor.
The researchers experimented with different sensor patterns, including squares, hexagons, pillars, and dots, and found that sensors with hexagonal patterns yielded the lowest on-skin impedance. I tested the sensor.
A hexagonal pattern sensor is placed on the occipital scalp to detect brain waves from the visual cortex, and the user wears an augmented reality (AR) lens that displays a white square. By concentrating on a particular square, brain waves are created that are picked up by biosensors. A decoder then converts that signal into a command.
User-worn augmented reality visor. A graphene sensor is attached to the scalp on the back.
University of Technology Sydney
“Our technology can issue at least nine commands in two seconds. It means you can.”
Soldiers of the Australian Army conducted real-world tests of the graphene sensor BMI and used it to control a four-legged robotic dog. The device allowed us to command the robot hands-free with up to 94% accuracy.
“Hands-free, voice-free technology works anywhere, anytime, outside the lab,” says Iacopi. “This eliminates the need for interfaces such as consoles, keyboards, touchscreens and hand gesture recognition.”
However, the researchers do not believe this is the final iteration of their design. Further research and testing is needed to strike a balance between the total available graphene area, the ability to respond to the presence of hair, and the ability to maintain contact between the scalp and the sensor.
However, this will not only have broader applications in advanced manufacturing, defense and aerospace, but will also lead to the development of technology that could greatly benefit people with disabilities when operating wheelchairs and prosthetic legs. This is a promising step towards
The study was published in a journal ACS applied nanomaterials.
Source: University of Technology, Sydney
