Lyra Martin Science 06.28.2022 07:Jun AM EDT

This Brain-machine Interface Helps a Man With Paralysis Feed Himself By Controlling Robotic Arms

The Johns Hopkins University researchers have created a brain-machine interface that controls robotic arms, enabling arm-paralyzed people to feed themselves.

UCSF researchers have built a brain-machine interface that can convert brain impulses into speech.

Paralyzed Men May Feed Themselves Through Robotic Arms

In the future, people with arm paralysis may simply feed themselves. Researchers from Johns Hopkins University have created a novel method that enables a partially paralyzed man to feed himself using robotic arms linked by a brain-machine interface.

Researchers from Johns Hopkins University have proven the capacity to "feel" virtual things by combining neural stimulation in a mixed-reality environment as part of a wider study studying neural multiplexing and novel modalities of perception made possible by the brain-computer interface (BCI).

Robert "Buz" Chmielewski, a research participant, has exhibited virtual tactile perception. Previously, he utilized a brain-machine interface to simultaneously operate two of the most sophisticated prosthetic limbs in the world and fed himself with two prosthetic limbs.

The investigation into the neural multiplexing-the degree to which the brain can accomplish typical perception and control through the senses and muscles at the same time as perception and control through a BCI-is a component of the Neurally Enhanced Operations (NEO) project, funded by the Defense Advanced Research Projects Agency.

When given particular commands, such as "choose cut position," he simply needed to make little fist motions to cause the fork and knife-equipped arms to cut and deliver food to his lips. According to the researcher, he could consume dessert in less than 90 seconds.

The new approach is based on a shared control scheme that reduces the mental effort needed to do a job. He could assign each of his two hand's four degrees of freedom to as many as 12 degrees while directing the robot arms. The limbs' prompt-based intelligent reactions also decreased the effort.

With Brain-Machine Interface, Scientists Aim to Restore Voices

Researchers at the University of California San Fransisco may also be able to restore voices using the fact that people with neurological diseases who lose the capacity to speak may still convey the brain signals necessary for speaking (such as the lips, jaw, and larynx).

They've created a brain-machine interface that converts brain impulses into voice. Instead of attempting to decipher thoughts, machine learning technology takes up nerve instructions and transforms them into a synthetic vocal tract.

The researchers aim to restore the voices of patients who have ALS, Parkinson's disease, and other illnesses where speech loss is often permanent. If that occurs, communication for such patients-who may now be forced to utilize considerably slower methods-could be much improved and even increase their sense of social integration.

According to the scientists, in the future, this method may not only enable people with a severe speech impairment to communicate fluently again, but it may also be able to mimic some of the melody of the human voice, which expresses the speaker's feelings and personality.