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NIH New Innovator Award recipient studying the use of artificial intelligence for paralysis

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Jennifer Johnson McEwen

Emory researcher Chethan Pandarinath is using artificial intelligence to build brain-machine interfaces to assist people with paralysis, specifically those with Amyotrophic Lateral Sclerosis. The NIH award will support a clinical trial launching this fall.

The National Institutes of Health (NIH) is awarding Chethan Pandarinath the 2021 Director’s New Innovator Award, an honor that recognizes exceptionally creative early career investigators.

Pandarinath, an assistant professor in the Wallace H. Coulter Department of Biomedical Engineering (Coulter BME), is using artificial intelligence to build brain-machine interfaces to assist people with paralysis, specifically those with Amyotrophic Lateral Sclerosis (ALS).

Part of the NIH’s High-Risk, High-Reward Research program, Pandarinath’s $2.4 million award grant will support his team’s launch of a clinical trial this fall, implanting sensors into the brains of paralyzed people with ALS. The sensors will use algorithms to help read complex nervous system signals that control movement and decode what the brain is telling the body to do in a matter of milliseconds. The goal of the five-year project will be to restore communication, hand function and speech in the trial participants.  

Pandarinath says the long-term goal is to reconnect the brain and the body for patients who are paralyzed not only from ALS but from strokes, spinal cord injuries or other serious neurological disorders.

“What NIH is looking for in this mechanism is ideas that they think are transformative — it's a little bit hard to predict how it will go, but the idea has the potential to really change an entire field. It’s wonderful recognition that they think my proposal is significant enough,” Pandarinath says. “And to move this toward a clinical trial, that really is a collaboration between Coulter BME and neurosurgery and neurology. That's pretty exciting. That's the only way we can make clinical impact.”

In addition to his role at Emory and Georgia Tech, Pandarinath is a faculty member in Emory's Department of Neurosurgery and the Emory Neuromodulation Technology Innovation Center, known as ENTICe. He will work closely with Emory neurosurgeons Nicholas Au Yong and Robert Gross and neurologist Jonathan Glass, director of the Emory ALS Center.

“It is exciting to see this project coming together as a result of the ingenuity and efforts of this extraordinarily talented team of engineers and clinician-scientists. It moves us closer toward our goal, in partnership with Georgia Tech, to improve the lives of patients disabled by ALS and other severe neurological disorders with ground-breaking innovations and discovery,” says Robert E. Gross, the MBNA Bowman Chair in Neurosurgery; professor, Emory University Department of Neurosurgery; and founder and director of ENTICe.

The Director’s New Innovator Award is only the second such award among Emory researchers since the program began in 2007. 

For the clinical trials, Pandarinath will pair AI tools with existing implantable brain sensors to test how well they work for patients. The implants are the kind of devices already used for deep brain stimulation for Parkinson’s patients, for example. The technology the team is developing is independent of the sensor — it is all about making the best use of the data recorded in the brain. 

These artificial intelligence tools have been reshaping other fields — for example, computer vision for autonomous vehicles, where AI must understand the surrounding environment, or teaching computers to play chess or complicated video games. Pandarinath has been working to apply unsupervised learning techniques to neuroscience and uncover what the brain is doing.

“We know these tools are changing the game in so many other AI applications,” Pandarinath says. We're showing how they can apply in brain-machine interfaces and impact people's health.”

Learn more about Pandarinath’s award:

AI Could Be the Key to Faster, Universal Brain-Machine Interfaces for Paralyzed Patients

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