(12,13) However, their use relies on applying a conductive gel electrolyte on the scalp and hair. (9−11) Ag/AgCl-based wet sensors are the reference in terms of performance among the noninvasive electrodes thanks to their low on-skin (∼5–30 kΩ at 50 Hz) impedance and high signal-to-noise (S/N) ratio (30 ± 5 dB). (6−10) Noninvasive sensors are often preferred when no severe disabilities are involved. (1,5) Among these, the sensing interface plays a crucial part by detecting the cortical electrical activity, which encodes human intent (brain waves at a frequency of ∼1–150 Hz), through either implanted (6,7) or wearable (8,9) neural sensors, such as electroencephalography (EEG) electrodes. (1−4) Such systems typically consist of three modules: an external sensory stimulus, a sensing interface, and a neural signal processing unit. Using these sensors, we have also demonstrated hands-free communication with a quadruped robot through brain activity.īrain–machine interfaces (BMIs) are hands-free and voice-command-free communication systems that allow an individual to operate external devices through brain waves, with vast potential for future robotics, bionic prosthetics, neurogaming, electronics, and autonomous vehicles. The patterned epitaxial graphene sensors show efficient on-skin contact with low impedance and can achieve comparable signal-to-noise ratios against wet sensors. The occipital region, corresponding to the visual cortex of the brain, is key to the implementation of BMIs based on the common steady-state visually evoked potential paradigm. 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. 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. However, dry sensors invariably show poorer performance compared to the gold standard Ag/AgCl wet sensors. The availability of accurate and reliable dry sensors for electroencephalography (EEG) is vital to enable large-scale deployment of brain–machine interfaces (BMIs).
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