Injury prevention is of critical concern for collegiate athletes, as musculoskeletal injuries can significantly impact short-term performance and long-term career sustainability. Athletes will greatly benefit from knowing if they are at an increased risk of injury during their required high-impact movements, such as when jumping and landing. However, early and accurate detection of injury risk factors during jumping is limited because objective biomechanical measurements do not account for any subjective user feedback when predicting injuries. Integrating objective and subjective measures into athlete monitoring protocols may lead to more accurate and individualized injury prediction. The overall objective of the proposed research is to determine the effectiveness of integrating objective biomechanical metrics of jumping with subjective metrics of exertion to identify injury risk factors for athletes who repeatedly perform high-impact jumping. Our overall hypothesis is that combining jump metrics derived from wearable inertial measurement units (IMUs) with an athlete’s perceived exertion scores will better predict injury risk factors for collegiate volleyball players and dancers.
Aim 1: Investigate the relationship between jump training intensity and patellar tendon health in female volleyball players.
Aim 2: Investigate the repeatability of IMUs in capturing jump metrics among elite collegiate dancers completing ballet and modern dance movements.
Committee Members:
- Siddhartha Sikdar, Professor, Bioengineering
- Samuel Acuña, Research Assistant Professor, Bioengineering
- Margaret Jones, Professor, School of Sports, Recreation and Tourism Management