Background
Motion analysis is critical for understanding injury mechanisms and enhancing prevention and rehabilitation strategies in sports medicine. Although conventional marker-based motion capture is effective for detailed biomechanical assessment, it is time-consuming, restricted to controlled environments, and susceptible to human error. Markerless motion capture offers greater convenience, enabling efficient data collection and on-site analysis. Nevertheless, its reliability for clinical applications requires validation.
Research question
This study investigates whether using the Theia3D markerless motion capture system yields different interpretations of subtalar joint kinematics during running compared to a marker-based system.
Methods
Fifteen recreational runners free of neuromuscular or musculoskeletal impairments were recruited. Previously collected treadmill running data were reprocessed using the updated Theia3D software, and the resulting subtalar joint kinematics were compared to those from the marker-based system. Statistical parametric mapping analysis and two-way within-subject repeated measures analysis of variance were used to determine differences between the two systems.
Results
Statistical parametric mapping revealed that Theia3D had systematic biases during different running speeds: overestimated subtalar frontal plane joint range of motion, maximal angular velocity, and maximal acceleration in the frontal plane compared to the marker-based system.
Significance
Given the association between subtalar joint kinematics and running-related injuries, we conclude that Theia3D provides convenience for clinical biomechanical studies but requires cautious interpretation for injury prediction and rehabilitation practices.
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