Wearable Brain-Machine Interface Turns Intentions into Actions

Georgia Institute of Technology

A new wearable brain-machine interface (BMI) system could improve the quality of life for people with motor dysfunction or paralysis, even those struggling with locked-in syndrome—when a person is fully conscious but unable to move or communicate.

A multi-institutional, international team of researchers at the Georgia Institute of Technology combined wireless soft scalp electronics and virtual reality in a BMI system that allows the user to imagine an action and wirelessly control a wheelchair or robotic arm.

The major advantage of this system to the user, compared to what currently exists, is that it is soft and comfortable to wear, and doesn’t have any wires.

BMI systems are a rehabilitation technology that analyzes a person’s brain signals and translates that neural activity into commands, turning intentions into actions. The most common non-invasive method for acquiring those signals is ElectroEncephaloGraphy, EEG, which typically requires a cumbersome electrode skull cap and a tangled web of wires.

These devices generally rely heavily on gels and pastes to help maintain skin contact, require extensive set-up times, are generally inconvenient and uncomfortable to use. The devices also often suffer from poor signal acquisition due to material degradation or motion artefacts—the ancillary “noise” which may be caused by something like teeth grinding or eye blinking. This noise shows up in brain data and must be filtered out.

The portable EEG system Yeo designed, integrating imperceptible microneedle electrodes with soft wireless circuits, offers improved signal acquisition. Accurately measuring those brain signals is critical to determining what actions a user wants to perform, so the team integrated a powerful machine learning algorithm and virtual reality component to address that challenge.

The new system was tested with four human subjects but hasn’t been studied with disabled individuals yet.

New Paradigm

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 many stimuli.

In the 2021 study, users demonstrated accurate control of virtual reality exercises using their thoughts—their motor imagery. The visual cues enhance the process for both the user and the researchers gathering information.

The virtual prompts have proven to be very helpful. They speed up and improve user engagement and accuracy. And we were able to record continuous, high-quality motor imagery activity.