Identifying Running Deviations in Long Distance Runners Utilizing Gait Profile Analysis: A Case Control Study

Abstract

Objective: The goal of this study was to utilize Gait Profile Score (GPS) and Gait Deviation Index (GDI), to assess its capability of differentiating between injured and non-injured runners. Design: In total, 45 long-distance runners (15 non-injured, 30 injured), diagnosed with one of the following running related injuries, patella femoral pain syndrome, iliotibial pain syndrome, and medial tibial stress syndrome, were recruited. Methods: Data were obtained from a running analysis gait laboratory equipped with eight infrared motion-capturing cameras and a conventional treadmill. Running kinematics were recorded according to the Plug-In Gait model, measuring running deviations of the pelvis and lower extremities at a sampling rate of 200 Hz. GPS and GDI were calculated integrating pelvis and lower limb kinematics. Movement Analysis Profile results were compared between injured and non-injured runners. The non-parametric two-sample Wilcoxson test determined whether significant kinematic differences were observed. Results: Total GPS score significantly differed between the injured and non-injured runners. Not all running kinematics expressed by GDI differed between groups. Conclusions: GPS score was capable of discriminating between the injured and non-injured runners’ groups. This new running assessment method makes it possible to identify running injuries using a single numerical value and evaluate movements in individual joints.

Keywords

• running
• gait analysis
• injury
• kinematics
• Gait Profile Score (GPS)