Micro-Doppler radars could soon be used to predict injury risk and track recovery

Micro-Doppler radars may soon be used in clinical settings to predict injury risk and track recovery progress, according to Penn State researchers.

Being able to see the subtle differences in human movement would allow healthcare workers to more precisely identify those at risk for injury and track progress accurately as people recover from an injury. In an effort to find an accurate, reliable, and cost-effective way to measure these subtleties in human movement, researchers from the College of Engineering and the College of Medicine have teamed up to develop a radar that athlete-subjects could jump past.

My students and I designed and built the radar system to characterize the micro-Doppler features of human gait, developed and tested various classification algorithms to separate patterns of different gait types, and validated our hypothesis using measured data from athletes imitating different walking patterns.

Ram Narayanan, Professor of Electrical Engineering, School of Electrical Engineering and Computer Science

The radar system relies on the Doppler effect – a way of measuring the change in wave frequency between a target and an observer – to provide accurate information about the movements of that target, in this case the athlete. This radar system could be an economical, portable and scalable alternative to motion capture systems, which are currently the most accurate system for showing subtle movements. However, they are too expensive, bulky, and time consuming to be a viable option in most situations.

“Micro-Doppler radar has not been used in healthcare at this point and is a new way of looking at human movement,” said Dr. Cayce Onks, associate professor of family and community medicine and orthopedics and rehabilitation at the College of Medicine and Physician at Penn State Health. “Our publication is the first of its kind to assess radar accuracy and predictability.”

The results were published in the journal Gait and Posture.

The study allowed NCAA athletes to jump barefoot past the radar, wearing shoes and wearing high-heel shoes. Radar was able to classify jumps into each of these three categories with greater than 90% accuracy, which existing motion capture systems cannot accomplish, according to Onks.

“The results of our study show that micro-Doppler radar is able to ‘see’ differences in human movement that the human eye is unable to differentiate,” said Onks. “This type of information has the potential to be applied to hundreds of clinical applications including, but not limited to, falls and disability prevention, early detection of Parkinson’s disease, detection early dementia, diagnosing concussions and identifying movement patterns that put individuals at risk. for any number of musculoskeletal injuries, such as ankle injuries and ACL tears. Other applications may include determining an individual’s readiness to resume movement after rehabilitation following injury or surgery. “

In order to further explore these possible applications, the researchers plan to apply for additional funding through the National Science Foundation and the National Institutes of Health.