Watch a person move a wheelchair using only their brain

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No one, not even José del R. Millán, expected Subject 1 to have a breakthrough when he did. The 26-year-old, who has tetraplegia with no mobility below the neck, had to be hospitalized midway through Millán’s studies due to an unrelated complication, and had completed more than 20 training sessions to operate a brain-controlled wheelchair without much to worry about. to show.

Yet he surprised everyone, including Millán, when something clicked into place during his last training sessions and he was able to control the wheelchair. He even navigated it with near-perfect accuracy through a cluttered room in a German clinic.

“We could never have predicted the breakthrough for subject 1,” Millán, a computer engineering and neurology researcher at the University of Texas at Austin, told The Daily Beast. “Everyone was super excited when we saw that kind of performance.”

Subject 1’s breakthrough is one of the key findings of a new study published Friday in the journal iSciencethat sheds new insight into the learning curve associated with technology connecting the human mind to machines – otherwise known as brain-computer interfaces (BCI).

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The study describes the training trajectories and performance of three people with tetraplegia while using a mind-controlled BCI wheelchair. They wore a cap with electrodes on their heads that allowed a computer to translate certain brain waves into commands for the wheelchair – the device would then move or turn based on the translated commands.

Subjects 1 and 3 eventually got the hang of using the wheelchair and navigated the hallway with ease. Meanwhile, subject 2 did not improve during training and could not control the wheelchair as easily.

These differences went beyond mere driving skills. By the end of the training, the people who improved had produced brain signals that an algorithm could more accurately translate into commands for the wheelchair. They also produced a command faster over time. In addition, connectivity – a measure of how well different brain regions can communicate – changed significantly over the course of training for Subjects 1 and 3, while it did not change for Subject 2.

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This variability is important for researchers to understand and share, so as not to pick positive findings, Millán said.

“We wanted to take up Subject 2’s case to show that there is no such thing as a magic bullet,” he said. “We need to have different options, and we also need to understand that the same intervention to two people won’t have the same effect.”

Most BCI studies to date have looked at people with disabilities who are not intended users of the assistive technologies in question. That’s why it was critical to enroll participants with disabilities in the study, Millán said.

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“I think watching people with tetraplegia is an important contribution because it’s not easy to work with them,” W. Hong Yeo, a biomechanical engineering researcher at Georgia Tech who was not involved in the study, told The Daily Beast. In general, he added, recruiting participants for a BCI study can be difficult due to the time-consuming nature of the training process and the squeamishness of people with electrode caps and sticky adhesive gel. People with tetraplegia often have complex health problems that may require hospitalization, and may not be interested in participating in exploratory or burdensome research.

Millán hopes to study the root cause behind BCI learning curves to ultimately speed up the learning process. For example, by finding out which factors led to the breakthrough of subject 1, he hopes that his research will lead to better assistive technologies for people with disabilities.

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