Advancing Carpal Tunnel Care with Machine Learning
The Hand Research Laboratory under the direction of Zong-Ming Li, PhD, vice chair for research in the Department of Orthopaedic Surgery, has been awarded $140,425 from the UArizona Office of Research, Innovation & Impact to advance the use of ultrasound imaging in evaluating the carpal arch, the floor of the carpal tunnel, which runs between hand and wrist.
Working with Xiaoxiao Sun, Ph.D., assistant professor in the Department of Epidemiology and Biostatistics at the Mel and Enid Zuckerman College of Public Health, Li is developing an algorithm that applies machine learning to carpal arch images to automatically identify and extract data embedded in the images.
Carpal tunnel syndrome is the most common condition of nerve entrapment, experienced by some 3–5% of U.S. adults per data from the Centers for Disease Control. The condition results when the median nerve that runs through the carpal tunnel becomes compressed, causing numbness, tingling and/or pain in the hand.