The technology, developed by Distinguished Professor Chin-Teng Lin and Professor Francesca Iacopi, in collaboration with the Australian Army and Defence Innovation Hub, has significant potential in a range of fields including advanced manufacturing, aerospace, and healthcare.
“By using cutting edge graphene material, combined with silicon, we were able to overcome issues of corrosion, durability and skin contact resistance, to develop the wearable dry sensors,” said Professor Iacopi.
The technology was recently demonstrated by the Australian Army, where soldiers operated a Ghost Robotics quadruped robot using the brain-machine interface. The device allowed hands-free command of the robotic dog with up to 94% accuracy.
“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,” Professor Lin said.
The researchers believe the technology will be of interest to the scientific community, industry and government, and hope to continue making advances in brain-computer interface systems.
“This is a major breakthrough that could revolutionize the way we interact with machines and devices,” said Professor Iacopi. “It has the potential to transform the lives of people with disabilities, allowing them to control prosthetics and wheelchairs with their thoughts. It could also have a significant impact on industries such as manufacturing, where it could enable workers to operate machinery more efficiently and safely.”
The technology uses hexagon patterned sensors that are positioned over the back of the scalp, to detect brainwaves from the visual cortex. The sensors are resilient to harsh conditions so they can be used in extreme operating environments.
“The hands-free, voice-free technology works outside laboratory settings, anytime, anywhere. It makes interfaces such as consoles, keyboards, touchscreens and hand-gesture recognition redundant,” said Professor Iacopi.
The researchers hope that their work will lead to further advances in brain-computer interface systems, and that the technology will become more widely available in the coming years.