Brain–computer interfaces (BCIs) enable the flow of information between the brain and an external device such as a computer, smartphone or robotic limb. Applications range from use in augmented and virtual reality (AR and VR), to restoring function to people with neurological disorders or injuries.
Electroencephalography (EEG)-based BCIs use sensors on the scalp to noninvasively record electrical signals from the brain and decode them to determine the user’s intent. Currently, however, such BCIs require bulky, rigid sensors that prevent use during movement and don’t work well with hair on the scalp, which affects the skin–electrode impedance. A team headed up at Georgia Tech’s WISH Center has overcome these limitations by creating a brain sensor that’s small enough to fit between strands of hair and is stable even while the user is moving.
“This BCI system can find wide applications. For example, we can realize a text spelling interface for people who can’t speak,” says W Hong Yeo, Harris Saunders Jr Professor at Georgia Tech and director of the WISH Center, who co-led the project with Tae June Kang from Inha University in Korea. “For people who have movement issues, this BCI system can offer connectivity with human augmentation devices, a wearable exoskeleton, for example. Then, using their brain signals, we can detect the user’s intentions to control the wearable system.”
Easily removable. I prefer that.
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