Universal brain-computer interface allows people to play games with just their thoughts

AUSTIN, Texas – Imagine playing a racing game like Mario Kart, using only your brain to execute the complex series of turns in a lap.

This is no video game fantasy, but a real program that engineers at the University of Texas at Austin have created as part of research into brain-computer interfaces to help improve the lives of people with motor disabilities. Most importantly, the researchers incorporated machine learning capabilities with their brain-computer interface, making it a one-size-fits-all solution.

Typically, these devices require extensive calibration for each user—every brain is different, both for healthy and disabled users—and this has been a major barrier to mainstream adoption. This new solution can quickly understand the needs of an individual subject and self-calibrate through iteration. This means that many patients can use the device without having to tune it to the individual.

“When we think about it in a clinical setting, this technology will make it so that we won’t need a specialized team to do this calibration process, which is long and tedious,” said Satyam Kumar, a graduate student in José’s lab. del R. Millán, a professor in the Chandra Family Department of Electrical and Computer Engineering at the Cockrell School of Engineering and the Department of Neurology at the Dell Medical School. “It will be much faster to go from patient to patient.”

From left to right: Satyam Kumar, Hussein Alawieh and José del R. Millán.

Research on the calibration-free interface is published in PNAS Nexus.

Subjects wear a cap filled with electrodes that is connected to a computer. The electrodes collect data by measuring electrical signals from the brain, and the decoder interprets that information and translates it into game action.

Millán’s work on brain-computer interfaces helps users direct and strengthen their neural plasticity, the brain’s ability to change, grow and reorganize over time. These experiments are designed to improve brain function for patients and use devices controlled by brain-computer interfaces to make their lives easier.

In this case, the actions were twofold: the car racing game and a simpler task of balancing the left and right sides of a digital bar. An expert was trained to develop a “decoder” for the simplest tape task that makes it possible for the interface to translate brain waves into commands. The decoder serves as a baseline for other users and is the key to avoiding the lengthy calibration process.

The decoder worked well enough that subjects trained simultaneously on the grass game and the more complicated car racing game, which required thinking several steps ahead to make turns.

The researchers called this groundbreaking work, in that it sets the stage for further brain-computer interface innovation. This project used 18 subjects without motor impairment. Eventually, as they continue down this path, they will test this in people with motor impairments to apply it to larger groups in clinical settings.

“On the one hand, we want to translate BCI into the clinical field to help people with disabilities; on the other hand, we need to improve our technology to make it easier to use so that the impact for these people with disabilities is stronger,” said Millán.

On the translational side of the research, Millán and his team continue to work on a wheelchair that users can drive with a brain-computer interface. At the South by Southwest Conference and Festivals this month, researchers demonstrated another potential use of the technology, controlling two hand and arm rehabilitation robots. This was not part of the new paper, but a sign of where this technology could go in the future. Some people volunteered and succeeded in operating brain-controlled robots within minutes.

“The purpose of this technology is to help people, to help them in their daily lives,” Millán said. “We will continue this path wherever it takes us in our quest to help people.”

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