"Artificial intelligence (AI) machine learning is making a difference in assistive technology to help restore movement for the paralyzed. A new study in the American Institute of Physics journal APL Bioengineering shows how AI has the potential to restore lower-limb functions in those with severe spinal cord injuries (SCIs) by identifying patterns in brain signals captured noninvasively via electroencephalography (EEG)."
"An estimated 15 million people worldwide have spinal cord injury according to the World Health Organization. In the U.S., there are over 308,600 Americans living with traumatic spinal cord injury, and since 2015 78% of new cases are male according to the National Spinal Cord Injury Statistical Center. The lifetime cost for a 25-year-old with high-level quadriplegia, also known as high tetraplegia, can cost over USD 4.7 million according to the Christopher & Dana Reeve Foundation."
AI machine learning can identify patterns in noninvasive EEG signals to decode lower-limb motor attempts in people with severe spinal cord injuries. The approach establishes a baseline for EEG decoding of lower-limb motor attempts and enables development of brain-controlled neuroprosthetic systems. Four male participants aged 18–33 performed multiple sessions across weeks while seated in wheelchairs using a 64-channel EEG setup for data collection. Affiliated institutions included EPFL Lausanne, University Hospital Lausanne, Scuola Superiore Sant'Anna, and IRCCS Ospedale San Raffaele. Global estimates indicate around 15 million people with spinal cord injury and substantial lifetime costs for severe quadriplegia.
Read at Psychology Today
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