Big data techniques help paralyzed patient regain movement

Big data techniques help paralyzed patient regain movement

Big data techniques help paralyzed patient regain movement

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.

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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.

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“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.



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