Wearable BMI With VR Aims To Help People With Motor Dysfunction, Paralysis

A team of scientists and researchers has developed a new wearable brain-machine interface (BMI) system that aims to improve the quality of life of people with paralysis, motor dysfunction or even those who are fully conscious but can't communicate or move.

An international multi-institutional team of scientists and researchers led by Wan-Hong Yeo at the Georgia Institute of Technology created a device that combines wireless soft scalp electronics and virtual reality in a brain-machine interface system. The device enables users to imagine an action and control a robotic arm or wheelchair wirelessly.

The team described the new motor imagery-based brain-machine interface system in a paper published in the journal Advanced Science on July 17.

"The major advantage of this system to the user, compared to what currently exists, is that it is comfortable to wear, and doesn't have any wires," Yeo, who is an associate professor at George W. Woodruff School of Mechanical Engineering, said as per Science Daily.

The team designed a portable EEG system that includes imperceptible microneedle electrodes with soft wireless circuits to enhance the acquisition of signals. Moreover, they used a machine-learning algorithm and a virtual reality (VR) component to gauge brain signals and determine the actions the user wants to execute.

The wearable BMI with VR has been tested on four human subjects. The team, however, is yet to use it on patients with disabilities.

"This is just a first demonstration, but we're thrilled with what we have seen," Yeo further said.

The study is supported by the National Institutes of Health, the Center Grant (Human-Centric Interfaces and Engineering) at Georgia Tech, the Yonsei-KIST Convergence Research Program and the National Research Foundation of Korea.

Georgia Tech has already filed a patent application related to the wearable BMI with VR system.

In 2019, Ph.D. student Musa Mahmood worked on a wearable BMI capable of controlling a wheelchair, vehicle or computer.

"This new brain-machine interface uses an entirely different paradigm, involving imagined motor actions, such as grasping with either hand, which frees the subject from having to look at too much stimuli," Mahmood noted.

Mahmood also said future work on the system would center on optimizing electrode placement and more advanced incorporation of stimulus-based EEG based on what they learned from the previous two studies.