SBIR-STTR Award

A significant challenge within the DOD has been the ability to obtain precise evaluations of student skills mastery that also offers actionable intelligence for educational improvement. Without this performance data and metrics, skill deficiencies and educational gaps are often obscured until costly errors are made in real-world situations. Link to Learn will initially attempt to solve these training challenges in the medical space with B.E.A.S.T (Benchmark Evaluated Augmented Skills Training); the next evolution of warfighter assessment that quantifiably evaluates students against key performance indicators, while performing a variety of medical procedures. Using advanced motion capture and biometric data processed through machine learning algorithms, B.E.A.S.T can ultimately identify expert performance benchmarks which will then be used to evaluate student performance to identify individual strengths and weaknesses while tracking proficiency and skill mastery over time. Directly aligned with Technical Area (TA) 004, Link to Learn will determine the efficacy of the project and identify a highly motivated and engaged USAF end-user and supporting customer with a national defense related mission need in the area of Human Performance and Medical Technology R&D including rapid emergency medical response, trauma management, biological/cognitive research, and human capabilities; training, decision making, bioeffects, and human centered intelligence.

Tactical Combat Casualty Care for Medical Professionals (TCCC-MP) is the global standard for advanced prehospital casualty care. To increase survivability during the crucial golden hour, it is vital that life-saving emergency medicine skills and critical decision making are effectively mastered and maintained. The ability to obtain precise and actionable evaluation of skills proficiency, data retention, and applied learning for medical training is a current challenge within the DOD. Recent technological advances in hand tracking, eye tracking, and volumetric data collection will be utilized to develop BEAST to evaluate student performance against expert level benchmarks to identify individual strengths and weaknesses while tracking proficiency and skill mastery over time; directly aligned with TA-004 Human Performance, including Medical Technologies, rapid emergency medical response and trauma management and cognitive research and human capabilities including training, decision making, and human centered intelligence. Phase I efforts accomplished the development of a field-expedient and automated 3D motion scan data transformation pipeline for analysis by Machine Learning algorithms, and validation of BEAST’s technical feasibility. Currently engaged with DoD and non-defense customers nationwide, Link to Learn’s network of supporters is steadily growing into an elite group; all eagerly awaiting BEAST’s deployment to spearhead the next training revolution.