Abstract
BACKGROUND: Athletes prematurely cleared to play following concussion increase their risk for subsequent concussion and musculoskeletal injury, leading practitioners to call for low-cost and objective tools to identify lingering neuromotor control deficits following concussion. # PurposeThe purpose of this feasibility study was to determine the usefulness of Mizzou Point-of-care Assessment System (MPASS) measures for creating a discriminant model classifying individuals as being either healthy or in the post-acute phase of concussion (having suffered a concussion within the prior three months). STUDY DESIGN: Cross-sectional. METHODS: Ten participants with concussion injury (Mean = 3.9 ± 1.66 wks. post-concussion) and twelve with no concussion within the prior year participated in this study. All participants completed walking (normal, serial subtraction by seven, and head shaking), Romberg balance (eyes open and eyes closed on firm surface), and reaction time tasks while MPASS recorded kinematics, kinetics, and reaction time. Principal component analysis (PCA) was used to reduce the dimensionality of MPASS data. RESULTS: Using four retained principal components (PCs), the LDA model achieved a statistically significant (p = 0.007) accuracy of 82% with 80% sensitivity and 83% specificity for classifying participants into groups. CONCLUSION: This work presents a framework for assessing the discriminative power of multidimensional and clinically feasible tools for assessing human movement. LEVEL OF EVIDENCE: 3.