paralysis brain interface

Brain-interface computer allows paralysed people to type at unprecedented speed

A brain-computer interface that allows fast, accurate typing for people with paralysis has been developed by a Stanford University team.

Three study participants with severe limb weakness each had one or two aspirin-sized electrode arrays placed in their brains to record signals from the motor cortex, a region controlling muscle movement.

These signals were transmitted to a computer via a cable and translated by algorithms into point-and-click commands guiding a cursor to characters on an onscreen keyboard.

Each participant, after minimal training, mastered the technique sufficiently to outperform the results of any previous test of brain-computer interfaces (BCIs) for enhancing communication by people with similarly impaired movement.

Notably, the study participants achieved these typing rates without the use of the automatic word-completion assistance common in electronic keyboarding applications nowadays, which likely would have boosted their performance.

One participant, Dennis Degray of Menlo Park, California, was able to type 39 correct characters per minute, equivalent to about eight words per minute.

This point-and-click approach could be applied to a variety of computing devices, including smartphones and tablets, without substantial modifications, the Stanford researchers said.

“Our study’s success marks a major milestone on the road to improving quality of life for people with paralysis,” said Jaimie Henderson, professor of neurosurgery, who performed two of the three device-implantation procedures.

“This study reports the highest speed and accuracy, by a factor of three, over what’s been shown before,” said Krishna Shenoy, a Howard Hughes Medical Institute investigator who’s been pursuing BCI development for 15 years. “We’re approaching the speed at which you can type text on your cellphone.”

Shenoy’s lab pioneered the algorithms used to decode the complex volleys of electrical signals fired by nerve cells in the motor cortex, the brain’s command centre for movement, and convert them in real time into actions ordinarily executed by spinal cord and muscles.

Patient Degray received two device implants at Henderson’s hands in August 2016. In several subsequent research sessions, he and the other two study participants, who underwent similar surgeries, were encouraged to attempt or visualise patterns of desired arm, hand and finger movements.

Resulting neural signals from the motor cortex were electronically extracted by the embedded recording devices, transmitted to a computer and translated by Shenoy’s algorithms into commands directing a cursor on an onscreen keyboard to participant-specified characters.

The researchers gauged the speeds at which the patients were able to correctly copy phrases and sentences such as, “The quick brown fox jumped over the lazy dog.” Average rates were 7.8 words per minute for Degray and 6.3 and 2.7 words per minute, respectively, for the other two participants.

The investigational system used in the study, an intracortical brain-computer interface called the BrainGate Neural Interface System, represents the newest generation of BCIs. Previous generations picked up signals first via electrical leads placed on the scalp, then by being surgically positioned at the brain’s surface beneath the skull.

An intracortical BCI uses a tiny silicon chip, just over one-sixth of an inch square, from which protrude 100 electrodes that penetrate the brain to about the thickness of a quarter and tap into the electrical activity of individual nerve cells in the motor cortex.

Henderson likened the resulting improved resolution of neural sensing, compared with that of older-generation BCIs, to that of handing out applause meters to individual members of a studio audience rather than just stationing them on the ceiling, “so you can tell just how hard and how fast each person in the audience is clapping.”

Shenoy said the day will come - closer to five years from now, rather than 10, he predicted - when a self-calibrating, fully implanted wireless system can be used without caregiver assistance, with no cosmetic impact on the recipient and which can be used around the clock.

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