Big data is able to do more than just enable hospital administrators to find new efficiencies or treatment protocols—it also has the potential to give paralyzed patients the ability to move.

The use of millions of data points generated each second is enabling a paralyzed man to regain function in his limbs, allowing him to perform fine-motor tasks such as swiping a credit card or playing guitar video games.

The capability is still being studied, and the devices needed to make movement possible are too large to give paralyzed individuals the ability to use it outside a research setting. But, it does serve as proof that technology might provide a workaround that will return movement and function to their lives.

The technology is being developed by Battelle, a not-for-profit research and development organization, working in partnership with The Ohio State University Wexner Medical Center. Dubbed NeuroLife, the technology creates a neural bypass that turns the patient’s thoughts into signals that bypass an injured spinal cord.

Ian Burkhart , paralyzed from the shoulders down after a diving accident, has regained functional use of his hand through the use of neural bypass technology.
Ian Burkhart , paralyzed from the shoulders down after a diving accident, has regained functional use of his hand through the use of neural bypass technology.

Key to the success of the research is the use of big data techniques to process nearly 3 million data points generated every second by the patient’s brain.

The program is part of a study approved by the Food and Drug Administration, says Michael Schwemmer, Ph.D., a data analytics expert at Battelle. The project began in 2014, when Ian Burkhart, a quadriplegic injured in a diving accident, underwent voluntary surgery to have a micro-electric chip implanted in his brain at Wexner Medical Center, enabling Battelle researchers to record his brain signals.

“What we get out of that chip is a massive amount of data,” Schwemmer says, “with 96 channels in the chip sampling electric impulses, recording 30,000 data points per second, or a total of 2.8 million data points per second.”

Algorithms developed by Battelle sort through the data generated by the implanted chip to find those that are crucial to movement. They are then translated into movement commands that are relayed via action impulses to a sleeve, containing 160 electrodes, that is worn on the patient’s arm.

“We use a lot of machine learning to translate this massive amount of brain data into movements,” notes David Friedenberg, a principal research statistician for Battelle, which he describes as the world’s largest independent research and development organization. “Our strength is being able to call on several different engineering and technology disciplines.”

Through trial and error and by intensively working with the patient, Battelle researchers were able to determine how to regulate the impulses to achieve movement in the previously paralyzed limb.

For the past two years in hundreds of sessions at Wexner Medical Center, Burkhart has become more proficient at performing complex, functional tasks with his right hand as he learns the system and the system learns from him.

The system forms a neural bypass, says Nick Annetta, a researcher and electrical engineer at Battelle. “We’re able to turn Ian’s thoughts into signals that bypass his injured spinal cord, and send them directly to the sleeve, causing his muscles to move.”

“The brain of the participant and the limb muscles remain intact—the only thing that’s missing (because of the injury) is the connection,” Schwemmer adds. He says the secret sauce of the project is the technology that uses big data to translate electrical impulses in the brain and move it to the sleeve—and the perseverance of the patient in working with the system.

Burkhart plays a key role in this research, allowing the brain surgery for the implant, which “was not a trivial thing,” Schwemmer says. He has come in three times a week for three-hour sessions with the sleeve, enabling researchers to test which signals produced desired movements.

The project demonstrates the ability to use big data in the project, he adds. “It’s an interesting application of big data analytics techniques, and has value for people who have to deal with a big stream of data points quickly—they can learn from the techniques we use to make it manageable and pull out good insights.”

The research is a proof-of-concept at this point, and a number of hurdles remain before it can be used outside of a researcher environment, Schwemmer says. “The system is huge, and the electric stimulation system is hard to take with people. We want to shrink it down so it can be worn on a belt.”

Also, a patient’s emotions have been found to affect brain signals that govern movement, requiring recalibration of the system each day. “That would make it prohibitive for home use—no one would want to spend 10 to 15 minutes each day to make it work,” Schwemmer says.

But, after those hurdles are surmounted, the technology might have application in other areas, and Battelle is looking for potential commercialization opportunities for use to treat patients suffering from strokes or Parkinson’s disease.

Schwemmer will speak at HIMSS17, presenting a session entitled “Using Big Data to Reanimate a Paralyzed Limb,” at 1 p.m. Wednesday, February 22 in room 208C.

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