Summary
Editor's Note: The following summary details independent academic research conducted in clinical research settings. Theia3D is an offline software solution engineered exclusively for research and human performance analysis.
Theresa E. McGuirk, Elliott S. Perry, Wandasun B. Sihanath, Sherveen Riazati and Carolynn Patten
Purpose
To determine the feasibility of markerless motion capture using Theia3D for three-dimensional gait biomechanics research in community-dwelling living domains.
Methods
The study included 166 individuals aged 9–87 years who completed walking trials at self-selected and fastest comfortable speeds across six community locations. In a subset of 46 participants aged 13–86 years, spatiotemporal gait parameters measured using Theia3D were compared with simultaneous measurements from a pressure-sensitive walkway.
Results
Markerless motion capture proved feasible across six community locations. In the 46-participant comparison, all 12 spatiotemporal gait parameters showed good to excellent agreement between Theia3D and the pressure-sensitive walkway, with particularly strong similarity in cadence, walking speed, step length, step time, stride length, and stride time.
Conclusion
Theia3D markerless motion capture is feasible for three-dimensional gait biomechanics research in community-dwelling living domains, supporting its use in large-scale, real-world movement research.
To read the full article in Frontiers in Human Neuroscience, click here.
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