Estimating Joint Contributions in Functional Motions to Create a Metric for Injury Prevention using Motion Capture and OpenSim: A Preliminary Study Alexander Kozlowski; Rebekah Koehn; Lauren Knop; Kelly Helm, PhD; Luis Prato, PT; Anthony Levenda, MD; Craig M. Goehler, PhD INTRODUCTION METHODS Majority of sports injury prevention studies focus on traumatic injuries such as concussion prevention and impact-related injuries. However, overuse and fatigue are the more predominant injury type in sports [1]. Such injuries occur in athletes with repeatedly incorrect biomechanics, improper conditioning, and poor stretching. Qualitative tests, such as the Landing Error Scoring System (LESS) and Functional Movement Screen (FMS) were developed to identify athletes that are at risk for an overuse injury [2, 3]. Human error in the form of inconsistent scoring and misdiagnosis of the motion can create unreliable data. The main objective of this project is to utilize quantitative techniques to measure human movement and develop training protocols that will result in more reliable data collection and analysis, reducing risk of athletic injury and improving performance. This initial study primarily focuses on studying joint mechanics of the lower extremity using the LESS test. Four subjects participated in the IRB approved study (3 male, 1 female). Reflective markers were placed on each subject’s lower extremity in specific anatomical locations (Figure A). VICON Nexus software was used to develop subject-specific models and collect motion capture data (Figure B). Each subject performed the LESS test several times while being recorded with the motion capture system for a total of 34 trials across all subjects. The data was filtered and exported as ASCII files for further analysis in OpenSim. A scaled musculoskeletal model was created for each subject and the inverse kinematic tool was utilized to determine the joint angles of the lumbar, hip, knee and ankle during each motion (Figure C). The data was further processed in MATLAB, normalized to a time of ten seconds, and compared across trials of the same test. RESULT AND DISCUSSION FUTURE WORK Inverse kinematics of each trial was used to determine hip flexion, hip adduction, hip rotation, knee flexion, ankle flexion, and lumbar extension throughout the motion. The mean and standard deviation of all trials across all four subjects were calculated for each joint angle and plotted against normalized time. Hip, knee, and ankle flexion were the main contributors to this motion, which occurred in the sagittal plane. Qualitative similarities between the right and left legs in all of the plots suggests that the average subject did not favor one leg over the other. Large standard deviation in lumbar extension suggests that there was a significant difference in the way each subject used his or her torso during the jump and landing. The preliminary metric from previous work consists of calculating the average and variation in joint configuration across the entire trial for hip flexion, knee flexion and ankle flexion [4]. Examine a series of functional motions including the LESS test, the FMS test, and additional jump tests. Expand study to looking at both lower and upper extremity joint angles. Develop a sufficient library of subject data to develop a statistical metric to be used as a baseline for comparisons. Support the data from this study with electromyography (EMG) data from the same trials. Test NCAA athletic teams at the beginning and throughout their respective season to detect improper biomechanics. REFERENCES 1. Clarsen B, et al. British Journal of Sports Medicine 47, 195, 1 May 2013. 2. Padua D, et al. The American Journal of Sports Medicine, 1-2, 2 Sept. 2009. 3. Grooms D, et al. Journal of Athletic Training, S79-S82, May 2014. 4. Honert E, et al. 7th World Congress of Biomechanics, July 2014. These values were combined for all trials across all subjects into a common group. There were no significant differences between the right and left legs, agreeing with the initial assessment of the plots. These results provide confidence for further work using this protocol.