title: Utilization of Practice Session Average Inertial Load to Quantify College Football Injury Risk.
abstract: Wilkerson, GB, Gupta, A, Allen, JR, Keith, CM, and Colston, MA. Utilization of practice session average inertial load to quantify college football injury risk. J Strength Cond Res 30(9): 2369-2374, 2016-Relatively few studies have investigated the potential injury prevention value of data derived from recently developed wearable technology for measurement of body mass accelerations during the performance of sport-related activities. The available evidence has been derived from studies focused on avoidance of overtraining syndrome, which is believed to induce a chronically fatigued state that can be identified through monitoring of inertial load accumulation. Reduced variability in movement patterns is also believed to be an important injury risk factor, but no evidence currently exists to guide interpretation of data derived from inertial measurement units (IMUs) in this regard. We retrospectively analyzed archived data for a cohort of 45 National Collegiate Athletic Association Division 1-football bowl subdivision football players who wore IMUs on the upper back during practice sessions to quantify any associations between average inertial load measured during practice sessions and occurrence of musculoskeletal sprains and strains. Both the coefficient of variation for average inertial load and frequent exposure to game conditions were found to be strongly associated with injury occurrence. Having either or both of the 2 risk factors provided strong discrimination between injured and noninjured players (χ = 9.048; p = 0.004; odds ratio = 8.04; 90% CI: 2.39, 27.03). Our findings may facilitate identification of individual football players who are likely to derive the greatest benefit from training activities designed to reduce injury risk through improved adaptability to rapidly changing environmental demands.
authors: 1Graduate Athletic Training Program, University of Tennessee at Chattanooga, Chattanooga, Tennessee; 2Analytics and Information Systems, Big Data & Analytics Research Center, University of Tennessee at Chattanooga, Chattanooga, Tennessee; and 3Sports Medicine, University of Alabama, Tuscaloosa, Alabama.
authors: Gary B
authors: GB
authors: Wilkerson
authors: Ashish
authors: A
authors: Gupta
authors: Jeff R
authors: JR
authors: Allen
authors: Clay M
authors: CM
authors: Keith
authors: Marisa A
authors: MA
authors: Colston
mesh_terms: D000054:Acceleration; D000293:Adolescent; D001265:Athletic Injuries / Q000175:diagnosis* / Q000503:physiopathology / Q000517:prevention & control; D015444:Exercise / Q000502:physiology*; D005538:Football / Q000293:injuries*; D006801:Humans; D008297:Male; D055617:Micro-Electrical-Mechanical Systems / Q000295:instrumentation / Q000379:methods*; D012372:ROC Curve; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D013180:Sprains and Strains / Q000175:diagnosis* / Q000503:physiopathology / Q000517:prevention & control; D014495:Universities; D055815:Young Adult