HomeLatest ArticlesResearchers modified commercial virtual reality headset to measure brain activity and study...

Researchers modified commercial virtual reality headset to measure brain activity and study how we respond to external factors

Researchers modified a commercial virtual reality headset to measure brain activity and study how we respond to cues, stressors and other external forces. A research team from the University of Texas at Austin has created a non-invasive electroencephalogram (EEG) sensor that they installed in a Meta VR headset that can be worn comfortably for long periods of time. EEG measures the brain’s electrical activity during immersive VR interactions.

The device could be used in many ways, from helping people with anxiety, to measuring the attention or psychological stress of pilots using a flight simulator, to being able to see through the eyes of a robot.

Nanshu Lu, a professor in the Cockrell School of Engineering’s Department of Aerospace Engineering and Engineering Mechanics who led the research says “Virtual reality is much more immersive than just doing something on a big screen,” said, It gives the user a more realistic experience, and our technology allows us to get better measurements of how the brain is responding to that environment.”

The pairing of VR and EEG sensors has already made its way into the commercial sphere. However, the devices that exist today are expensive, and researchers say their electrodes are more comfortable for users, increasing potential wear time and opening up other applications.

The best EEG devices today consist of a cap covered with electrodes, but that doesn’t work well with a VR headset. And individual electrodes struggle with strong measurements because our hair blocks their connection to the scalp. The most popular electrodes are rigid and comb-shaped, inserted into the hair to connect with the skin, which is an unpleasant experience for the user.

Hongbian Li, a researcher in Lu’s lab said “All of these mainstream options have significant shortcomings, which we tried to overcome with our system”.

For this project, the researchers created a sponge-like electrode made of soft, conductive materials that overcome these problems, an effort led by Li. The modified headset includes electrodes over the top strap and forehead pad, a flexible circuit with conductive traces similar to Lu’s electronic tattoo, and an EEG recording device attached to the back of the headset.

The technology will play a role in another major research project at UT Austin:

A New Robotic Delivery Network, which will also serve as the largest human-robot interaction study to date. Lu is part of this project, and VR headsets will be used by people traveling with robots or in remote “observatories.” They will be able to observe from the robot’s point of view, and the device will also measure the psychological burden of this observation over a long period of time.

“If you can see through the robot’s eyes, it paints a clearer picture of how people react to it and allows operators to monitor their safety in the event of potential accidents,” said Luis Sentis, a professor in the Department of Aeronautical Engineering and Engineering Mechanics who co-authored the robot delivery project and is co-author of the VR EEG article.

To test the viability of a VR EEG headset, the researchers created a game. They collaborated with José del R. Millán, a faculty member in the Chandra Family Department of Electrical and Computer Engineering and the Dell School of Medicine and an expert in brain-machine interfaces, to develop a driving simulation in which the user can respond by pressing a button. to rotate commands.

EEG measures the brain activity of users

EEG measures the brain activity of users when making driving decisions. In this case, it shows how carefully subjects are paying attention.

The researchers have filed preliminary patent documentation for EEG and are open to partnering with VR companies to create an embedded version of the technology.

Other members of the research team include Hyonyoung Shin, Minsu Zhang, Nicholas Riveira, and Susmita Gangopadahyay from the Chandra Family Department of Electrical and Computer Engineering; Andrew Yu, Heeyong Huh, Zhengjie Li and Yifan Rao from the Department of Aerospace Engineering and Engineering Mechanics; Sangjun Kim of Walker’s Department of Mechanical Engineering, Jessie Peng of the Department of Biomedical Engineering; and Gubeum Kwon of Artue Associates Inc. in South Korea.

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Reference: https://www.sciencedaily.com/releases/2023/08/230804140510.htm

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