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A team of researchers at the Johns Hopkins Applied Physics Laboratory (APL – Laurel, Maryland) is developing a system to monitor physical fatigue and possible injury in soldiers in near-real time using body-worn sensors and machine learning (ML) algorithms.

Machine learning technology could soon report in real time whether soldiers need a break and identify who is at risk for injury.

The system tracks aerobic and anaerobic exercises to predict the risk of musculoskeletal injuries and protect those who are at high risk for injuries