Sensor classified neural signals with over 96% accuracy
The sensor developed by Georgia Tech uses extremely small microneedles which are imperceptible to the user. These sensors are also wireless and flexible, removing the need for conductive gel to work.
This combination of factors lets the sensor stay in place all day, even if the wearer walks, runs, or performs other daily tasks. Because of this, the sensor can get closer to brain signals and collect cleaner, more accurate data.
When tested, the new sensor successfully recorded and classified neural signals indicating the objects the user focused on in the environment with 96.4% accuracy. Wearers could also browse through phone logs and accept augmented reality video calls completely hands free because the sensor was picking up visual stimuli.