Micro-Doppler radars could soon be used in clinical settings to predict injury risk and monitor recovery progress, according to Penn State researchers.
Seeing subtle differences in human movement would allow healthcare workers to more accurately identify people who may be at risk of injury and monitor progress directly while people are at risk. half recovering from an injury. In an effort to find an accurate, reliable, and cost-effective way to measure these symptoms in human movement, researchers from the College of Engineering and the College of Medicine came together to develop a radar on which athletes ’study subjects could jump.
“My students and I designed and built the radar system to identify the micro-Doppler features of a human gait, developing and testing several classification algorithms to separate patterns from different foot types and determine our hypothesis uses measured data from athletes that resembled different leg patterns, ”said Ram Narayanan, professor of electrical engineering in the School of Electrical Engineering and Computer Science.
The radar system relies on the Doppler effect – a method of measuring the change in wave frequency between a target and an observer – to provide detailed information about the movements of that target, in this case, the athlete. This radar system could be a cost-effective, portable and scalable alternative to motion capture systems, which are currently the most accurate system for showing subtle motion movements. However, they are too expensive, bulky and time consuming to use to be a viable option in most situations.
“The micro-Doppler radar has not been used in health care to date and is a new way to monitor human movement,” said Dr. Cayce Onks, associate professor of family medicine. and community and orthopedics and rehabilitation in the College of Medicine, and a physician at Penn State Health. “Our publication is the first of its kind to assess the accuracy and prediction of radar.”
The results were published in the journal Gait and Posture.
The study of NCAA athletes jumping in front of the radar barefoot, wearing shoes, and wearing shoes with heel lift. The radar was able to sort the jerseys into each of the three categories with an accuracy greater than 90%, something that the current capture capture systems cannot achieve, according to Onks.
“The findings of our study show that the micro-Doppler radar is capable of detecting differences in human motion that the human eye cannot make a difference,” Onks said. “This type of information has the potential to be applied to hundreds of clinical applications, including but not limited to the prevention of falls and disabilities, early detection of Parkinson’s Disease, depression early detection, decision diagnosis and identification of movement patterns that put people at risk for any number of muscle injuries, such as ankle injuries and ACL tears. Other claims may include determining a person’s willingness to return to motion after recovering from an injury or surgery. ”
To further explore these potential applications, the researchers plan to apply for additional funding through the National Science Foundation and the National Institutes of Health.
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Magazine Reference:
Onks, C., et al. (2021) Accuracy and prediction of Doppler’s signature radar prediction algorithm measuring action movement in NCAA athletes. Gait & Posture. doi.org/10.1016/j.gaitpost.2021.01.021.