What happens when you combine advanced robotics with the mutant powers of Professor X and fashionable headwear? You get a state-of-the-art headband that allows the wearer to control robots and other machines with their mind. The industrial applications of this technological advancement are limitless. At the plant, you could alter multiple production lines with just a thought. At the warehouse, you could seamlessly direct your automated guided vehicles like a conductor leading an orchestra. This might sound like a futuristic concept, but a new study illustrates just how close we are to applying brain-computer interface technology in everyday life.
In a study conducted by researchers at the University of Technology Sydney (UTS), Distinguished Professor Chin-Teng Lin and Professor Francesca Iacopi, developed the biosensor technology that allows users to use their thoughts to control robots. The project was developed with assistance from the Australian Army and Defence Innovation Hub. To make this unique technology possible, hexagon-patterned graphene sensors are placed over the back of the head, allowing the sensors to detect brainwaves from the visual cortex. In addition, the operator wears an augmented reality lens which displays white flickering squares. According to the researchers, when a wearer concentrates on a particular square, their brainwaves are detected by the biosensor, and a decoder translates the signal into commands.
The team’s findings were recently published in the ACS Applied Nano Materials in a paper titled “Noninvasive Sensors for Brain–Machine Interfaces Based on Micropatterned Epitaxial Graphene.” In an excerpt from the abstract, the authors explain how the device operates. “The availability of accurate and reliable dry sensors for electroencephalography (EEG) is vital to enable large-scale deployment of brain–machine interfaces (BMIs). However, dry sensors invariably show poorer performance compared to the gold standard Ag/AgCl wet sensors. The loss of performance with dry sensors is even more evident when monitoring the signal from hairy and curved areas of the scalp, requiring the use of bulky and uncomfortable acicular sensors. This work demonstrates three-dimensional micropatterned sensors based on a subnanometer-thick epitaxial graphene for detecting the EEG signal from the challenging occipital region of the scalp.”
In a recent quote, Professor Lin said, “Our technology can issue at least nine commands in two seconds. This means we have nine different kinds of commands and the operator can select one from those nine within that time period. We have also explored how to minimise noise from the body and environment to get a clearer signal from an operator’s brain.”