The idea of controlling a robot with your mind while wearing a customized electrical headband seems like something out of science fiction. However, current research that was just published in ACS Applied Nano Materials has made a step in the direction of making this a reality.

The team has developed "dry" sensors that can assess the electrical activity of the brain even when it is surrounded by hair and other head features like bumps and curves since they were able to produce a unique, 3D-patterned structure that is not dependent on sticky conductive gels.

Electroencephalography (EEG), in which specialized electrodes are either implanted into or put on the surface of the head, allows doctors to monitor electrical impulses from the brain. EEG is used in "brain-machine interfaces," which use brain waves to operate an external device, such as a prosthetic limb, robot, or even a video game, and which aid in the diagnosis of neurological illnesses.

The majority of non-invasive versions employ "wet" sensors, which are adhered to the head using a gooey gel that can irritate the scalp and occasionally cause allergic responses.

Researchers have been working on "dry" sensors that do not require gels as an alternative, but none have performed as well as the industry-standard wet kind up until this point.

Even while nanomaterials like graphene would be an appropriate choice, their flaky, flat nature makes them incompatible with the irregular curves of the human skull, especially over extended periods. Because of this, Francesca Iacopi and colleagues set out to develop a 3D graphene-based sensor based on polycrystalline graphene that could precisely and non-stickily track brain activity.

The group produced several 10 m thick, 3D graphene-coated objects with various forms and patterns. The curved, hairy surface of the occipital region, the area at the base of the skull where the brain's visual cortex is situated, responded best to a hexagonal arrangement of the forms evaluated.

Eight of these sensors were combined by the researchers into an elastic headband that kept them against the back of the head. The electrodes could recognize which visual cue was being observed when used in conjunction with an augmented reality headset that displayed visual cues, and then interact with a computer to translate the signals into instructions that controlled the mobility of a four-legged robot – fully hands-free.

Although the new electrodes didn't perform nearly as well as the wet sensors, the researchers claim that their study is a first step in creating reliable, straightforward dry sensors that will aid in extending the applications of brain-machine interfaces.

Funding: The authors thank the Australian Government's Defense Innovation Hub for financing the Australian National Fabrication Facility at the University of Technology Sydney as well as the University of Sydney Nano Institute's Research & Prototype Foundry.