Army looks to machine learning to predict, prevent injuries – GCN.com

Army looks to machine learning to predict, prevent injuries

The Army is harnessing a sensor and machine learning platform currently used by professional and collegiate sports teams to analyze individual soldiers biomechanics and predict and prevent physical injuries.

According to a March 2020 paper in Military Medicine, noncombat injuries are the leading cause of outpatient medical visits among active Army service members, accounting for nearly 60% of soldiers limited duty days and 65% of soldiers who cannot deploy for medical reasons. Besides decreasing the number of soldiers available to deploy, these injuries are expensive to treat and can lead to service-connected disability compensation.

The Armys Mission and Installation Contracting Command will be using Sparta Sciences Sparta Trac system to collect data on movements used in heavy physical training regimes. The system uses force plates, similar to large bathroom scales that are equipped with sensors that assess an athletes core and lower extremity strength. As athletes do various balance, jumping and plank exercises, the system collects and analyzes the data to create a movement signature and show the risk level for musculoskeletal injuries. It also designs customized workouts so soldiers can strengthen weak areas and avoid injuries. The diagnostic test takes five minutes, company officials wrote in an Aug. 18 column for Stars and Stripes.

Force plate technology was singled out for study by the military in the 2021 National Defense Authorization Act. The NDAA encouraged development of a tool that will check warfighters physical fitness to determine combat readiness. Force plate technology and machine learning capabilities are an important part of that tool, according to the NDAA.

Although force plate systems are already used across the military, the NDAA tasked the Secretary of Defense to report on how many military units are using the systems, as well as whether the technology could be scaled to develop individual fitness programs for at-home and deployed warfighters.

About the Author

Mark Rockwell is a senior staff writer at FCW, whose beat focuses on acquisition, the Department of Homeland Security and the Department of Energy.

Before joining FCW, Rockwell was Washington correspondent for Government Security News, where he covered all aspects of homeland security from IT to detection dogs and border security. Over the last 25 years in Washington as a reporter, editor and correspondent, he has covered an increasingly wide array of high-tech issues for publications like Communications Week, Internet Week, Fiber Optics News, tele.com magazine and Wireless Week.

Rockwell received a Jesse H. Neal Award for his work covering telecommunications issues, and is a graduate of James Madison University.

Click here for previous articles by Rockwell. Contact him at [emailprotected] or follow him on Twitter at @MRockwell4.

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Army looks to machine learning to predict, prevent injuries - GCN.com

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