Jul 19, 2026

Feinstein Institutes’ double neural bypass restores movement and touch to a paralysed patient

Holographic robot beside a patient diagram illustrating a double neural bypass brain-computer interface restoring movement and touch

Researchers at the Feinstein Institutes for Medical Research have restored hand movement and the sense of touch to a man paralysed from the chest down, with results pointing to lasting rewiring of his nervous system. The findings, published in Nature Medicine, describe a system the team calls a “double neural bypass” that combines a brain-computer interface, AI, and targeted electrical stimulation of the spinal cord and brain.

What the participant regained

The participant, Keith Thomas, broke his neck in a 2020 diving accident and lived with complete tetraplegia, unable to lift his hands to his face. He enrolled in the three-year trial 13 months after his injury.

After training, Thomas could feed himself and drink from a cup using his own hand. Over 35 weeks, his right arm grew 86% stronger and his left arm 62% stronger, according to the researchers. He was also able to scratch his nose and wipe his mouth unaided.

A separate technique, which the team calls cortical mirroring, targeted the sense of touch. After roughly 25 weeks, Thomas reported feeling in a wrist that had been numb since his injury.

Why the lasting effect matters

Many of the gains held after the electrical stimulation stopped. On a recent follow-up more than two years later, the improvements were still present. The team interprets this as evidence of neuroplasticity, the nervous system reorganising itself rather than relying on a temporary assist.

“We’re not just bypassing the injury; we’re actually rewiring the nervous system,” said Chad Bouton, the study’s corresponding author, in a statement. “For me this is an incredible moment,” he added in comments to The Guardian.

For Thomas, the sensory gains were especially meaningful. “Being able to feel my sister’s hand, to pet my dog and feel her fur, these experiences that the injury took away have been restored,” he said.

How the double neural bypass works

During a 15-hour operation, surgeons implanted five microelectrode arrays in Thomas’s brain. AI decodes his intended movements and triggers stimulation of his forearm muscles so that his own hand moves. Sensors in a 3D-printed brace, in turn, stimulate the sensory cortex to create the feeling of touch.

The decoder held up to 84.6% accuracy over five months without retraining. In a delicate test of motor control, Thomas could lift empty eggshells without breaking them 87% of the time, even while holding a conversation.

Where the research sits in the wider field

The work adds to a fast-moving area of brain-computer interface research. Rival groups have used implants to restore speech, while others pursue wearable or non-invasive approaches. China has also cleared its first commercial brain implant.

According to background figures cited in the report, about 15 million people live with spinal cord injury worldwide, and most people with tetraplegia rate hand function as their top priority. The Feinstein Institutes team plans larger trials and is testing the system for other conditions, including stroke.

The study was published in Nature Medicine on July 16, 2026.

FAQ

What is a double neural bypass?

It is the name the Feinstein Institutes team gave to a system that combines a brain-computer interface, AI decoding of movement intent, and electrical stimulation of the spinal cord and brain. It was used to restore both movement and touch in a participant with complete tetraplegia.

How long did the effects last after stimulation stopped?

Researchers reported that many of the participant’s gains, including arm strength and sensation in his wrist, were still present more than two years after the last stimulation sessions, which they describe as evidence of neuroplasticity.

What were the participant’s measurable improvements?

Over 35 weeks of training, his right arm grew 86% stronger and his left arm 62% stronger. The decoder maintained up to 84.6% accuracy over five months without retraining, and he could lift empty eggshells without breaking them 87% of the time, even while talking.


This article summarizes reporting from thenextweb.com.