Traumatic and debilitating anterior cruciate ligament (ACL) injuries occur at a 2- to 10-fold greater rate in female than male athletes, and 50-100% of females develop knee osteoarthritis within 12-20 years of initial injury. The National Public Health Agenda for Osteoarthritis recommends expanding and refining evidence- based prevention of ACL injury to reduce this burden. We have identified modifiable risk factors that predict ACL injury in young female athletes. Our lab-based neuromuscular training targets modifiable risk factors and shows statistical efficacy in high-risk athletes, but a meaningful risk re-categorization to low-risk has not been achieved. Standard interventions may be inefficient for biomechanical adaptation, susceptible to non- compliance, and limited in translation to injury risk reductions; current approaches have not yet decelerated national ACL injury rates in young female athletes. The key gap in knowledge is how to deliver objective, individualized, analytic feedback efficiently and effectively for injury prevention training. The overall objective of this proposal is to implement and test innovative augmented neuromuscular training (aNMT) methods to enhance sensorimotor learning and more effectively reduce biomechanical risk factors for ACL injury. aNMT biofeedback integrates biomechanics screening with portable augmented reality glasses to display real-time feedback, which maps complex biomechanical variables onto simple visual stimuli that athletes intuitively control via their own movements. Our published and new preliminary data on aNMT demonstrate our proficiency in implementing this technology and the efficacy of the approach to efficiently induce desired training adaptations. The data support this proposal's central hypothesis: Sensorimotor biofeedback will improve localized joint mechanics and reduce global injury risk in evidence-based measures collected in laboratory tasks and in realistic, sport-specific virtual reality scenarios. Once the objectives of this application are achieved, we expect to both optimize the efficiency and enhance the efficacy of feedback for personalized and targeted injury prevention, and establish the potential for enhanced sensorimotor adaptions from aNMT to translate to the field of play. The removal of barriers to feedback interventions (e.g., the need for qualified instructors who provide subjective, possibly erroneous or unclear feedback) via real-time automated, implicit, and analytic-driven biofeedback could revolutionize ACL injury prevention. The positive impact of such innovative strategies will be enhanced delivery of biofeedback with increased potential for sport transfer. This contribution will be significant for ACL injury prevention and associated long-term sequelae in young females. It will also likely benefit injury prevention strategies for males, enhance motor development programs for children, and impact rehabilitation strategies in orthopedic clinical practice.
The proposed research is relevant to public health because discovery of successful knee injury prevention techniques will lead to fewer young women who sustain knee injuries; this is currently a major long term individual and public health problem in the United States. The project is relevant to NIH's mission because the knowledge gained will be used to optimize prevention strategies that will enhance health and reduce the burdens of knee injuries that afflict women disproportionately compared to males.
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