Not Science Fiction: Paralyzed People Can Navigate Using Mind-Controlled Wheelchairs

Not Science Fiction: Paralyzed People Can Navigate Using Mind-Controlled Wheelchairs

Cyborg Brain Technology Mind Control Concept

In a new study, researchers demonstrate that tetraplegic users can operate mind-controlled wheelchairs in a natural, cluttered environment. The mind-controlled wheelchair helps paralyzed people gain new mobility by translating users’ thoughts into mechanical commands.

By translating users’ thoughts into mechanical commands, a mind-controlled wheelchair can help a paralyzed person gain new mobility. Researchers demonstrate that tetraplegic users can operate mind-controlled wheelchairs in a natural, cluttered environment after training for an extended period in a study published today (November 18) in the journal iScience.

“We show that mutual learning of both the user and the brain-machine interface algorithm are both important for users to successfully operate such wheelchairs,” says José del R. Millán, the study’s corresponding author at The University of Texas at Austin. “Our research highlights a potential pathway for improved clinical translation of non-invasive brain-machine interface technology.”

Millán and his colleagues recruited three tetraplegic people for the longitudinal study. Each of the participants underwent training sessions three times per week for 2 to 5 months. The participants wore a skullcap that detected their brain activities through electroencephalography (EEG), which would be converted to mechanical commands for the wheelchairs via a brain-machine interface device. The participants were asked to control the direction of the wheelchair by thinking about moving their body parts. Specifically, they needed to think about moving both hands to turn left and both feet to turn right.


This video shows a participant operating a mind-controlled wheelchair across a cluttered room. Credit: Luca Tonin

In the first training session, three participants had similar levels of DOI: 10.1016/j.isci.2022.105418

This work was partially supported by the Italian Minister for Education and by the Department of Information Engineering of the University of Padova.

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