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AI compares medical rookies biomechanical skills to experts -- GCN

By GCN Staff Feb 26, 2021 To improve the quality of medical care for military service members, researchers are adopting artificial intelligence and markerless motion-capture technology to assess the biomechanical skills of medical trainees and provide feedback for improvement. “Simulation-based medical skill training, both initial and refresher training, require systematic, objective, high quality trainee evaluation and feedback,” the Army’s Medical Technology Enterprise Consortium said in a request for proposals. Unfortunately, MTEC said, evaluation and feedback on trainees’ performance are currently based on trainers’ standards rather than on an objective skill performance standard.   The Investigating Methods for Performance Overdrive (IMPROVE) program aims to address these assessment challenges. In December 2020, MTEC tapped the Southwest Research Institute (SwRI) to develop a simulation-based training system that compares the physical performance of medical traine

SwRI is developing machine vision tool to improve military medical training

SwRI is developing machine vision tool to improve military medical training Southwest Research Institute is developing a machine vision tool to help the U.S. Department of Defense assess the biomechanical movements of military medical personnel during training exercises. The simulation-based training system will compare medical trainee performance to that of experts whose physical motions, or kinematics, have been pre-recorded and analyzed in 3D with artificial intelligence. Military medical training relies on subjective human evaluations where feedback may vary among trainers, said Dr. Dan Nicolella, of SwRI s Mechanical Engineering Division, who co-leads the Institute s Human Performance Initiative with Kase Saylor, an Intelligent Systems Division manager. SwRI s research will help both instructors and trainees to objectively observe how well they are performing a specific task, providing both a quantitative score, based on expert task performance, and task-specific feedback t

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