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Mon 14 Apr 2025
Georgia Institute of Technology
Researchers have developed a micro-brain sensor that can be placed between hair follicles on the scalp to capture high-fidelity signals.
A brain-computer interface (BCI) is a direct communication link between the brain’s electrical activity and external devices, such as computers, robotic limbs and other brain-monitoring devices.
Most commonly, BCIs consist of electrodes mounted on the surface of the scalp to capture brain signals with conductive electrode gel enabling optimum impedance and data quality.
However, rigid sensors and bulky electronics mean these BCIs face significant limitations in terms of continuous use and portability.
Researchers from the Georgia Institute of Technology in Atlanta, US, have overcome these limitations by developing a wearable microneedle BCI wireless sensor that can be inserted into the spaces between hair follicles and slightly under the skin.
Hong Yeo, professor at Georgia Tech’s school of mechanical engineering and a faculty member of the Institute for People and Technology, said: “I started this research because my main goal is to develop new sensor technology to support healthcare and I had previous experience with brain-computer interfaces and flexible scalp electronics.
“I knew we needed better BCI sensor technology and discovered that if we can slightly penetrate the skin and avoid hair by miniaturising the sensor, we can dramatically increase the signal quality by getting closer to the source of the signals and reduce unwanted noise.”
The technology uses conductive polymer microneedles to capture electrical signals and conveys those signals along flexible polyimide/copper wires – all packaged in a space of less than a millimetre.
Georgia Institute of Technology
The researchers carried out a study of the micro BCI with six people who were using the device to control an augmented reality (AR) video call. The results showed that high-fidelity neural signal capture persisted for up to 12 hours, with very low electrical resistance at the contact between skin and sensor.
Participants would conduct daily activities, with the wearable BCI successfully recording and classifying neural signals, indicating which visual stimulus the user focused on with 96.4% accuracy.
During the testing, participants looked up phone contacts and initiated and accepted AR video calls hands-free as the micro-sized brain sensor picked up visual stimuli.
According to Yeo, the results suggest that this wearable BCI system may allow for practical and continuous interface activity, potentially leading to everyday use of machine-human integrative technology.
Yeo said: “I will now continue collaborating with the team to enhance BCI technology for rehabilitation and prosthetics.”
Earlier this month, researchers at Northwestern University revealed details about a millimetre-sized injectable pacemaker that is controlled using light shone through the skin, and dissolves when no longer needed.
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