Clinical Indoor Running Gait Analysis May Not Approximate Outdoor Running Gait Based on Novel Drone Technology

摘要

Background: Traditional running gait analysis is limited to artificial environments, but whether treadmill running approximates overground running is debated. This study aimed to compare treadmill gait analysis using fixed video with outdoor gait analysis using drone video capture.Hypothesis: Measured kinematics would be similar between natural outdoor running and traditional treadmill gait analysis. Study Design: Crossover study. Level of Evidence: Level 2.Methods: The study population included cross-country, track and field, and recreational athletes with current running mileage of at least 15 km per week. Participants completed segments in indoor and outdoor environments. Indoor running was completed on a treadmill with static video capture, and outdoor segments were obtained via drone on an outdoor track. Three reviewers independently performed clinical gait analysis on footage for 32 runners using kinematic measurements with published acceptable intra- and interrater reliability.Results: Of the 8 kinematic variables measured, 2 were found to have moderate agreement indoor versus outdoor, while 6 had fair to poor agreement. Foot strike at initial contact and rearfoot position at midstance had moderate agreement indoor versus outdoor, with a kappa of 0.54 and 0.49, respectively. The remaining variables: tibial inclination at initial contact, knee flexion angle initial contact, forward trunk lean full gait cycle, knee center position midstance, knee separation midstance, and lateral pelvic drop at midstance were found to have fair to poor agreement, ranging from 0.21 to 0.36.Conclusion: This study suggests that kinematics may differ between natural outdoor running and traditional treadmill gait analysis.Clinical Relevance: Providing recommendations for altering gait based on treadmill gait analysis may prove to be harmful if treadmill analysis does not approximate natural running environments. Drone technology could provide advancement in clinical running recommendations by capturing runners in natural environments.