New Markerless Gait Biomechanics Research Validation Study!

May 1, 2024
Theia
BIO
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Summary

New research on the repeatability of gait outcomes in study participants with knee osteoarthritis using Theia3D's markerless motion capture system demonstrates strong test-retest reliability for key biomechanical parameters.

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.

New research on the repeatability of gait outcomes in participant(s) with knee osteoarthritis using markerless motion tracking has just been published! The lead author, Jereme Outerleys, conducted this research at the Queen’s University Human Mobility Research Lab using Theia3D to measure and analyze gait across multiple subjects. The full publication can be found in the Journal of Biomechanics.

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Abstract

Motion analysis has seen minimal adoption for orthopaedic research assessments. Markerless motion capture solutions, namely Theia3D, address limitations of previous methods and provide gait outcomes that are robust to clothing choice and repeatable in healthy adults. Repeatability in orthopaedic research populations has not been investigated and is important for research utility and adoption. The purpose of this study was to evaluate the repeatability of Theia3D for gait biomechanics research in a knee osteoarthritis population. Ten research participants with knee osteoarthritis underwent gait biomechanics research on three visits, with an average of 8 days between. Participants were recorded during one-minute overground walking trials at self-selected typical and fast speeds by 8 synchronized video cameras. Video data were processed using Theia3D. Intraclass correlations were used to examine the repeatability of temporal distance metrics as well as segment lengths of the underlying kinematic model. Inter-trial and inter-session variability of lower extremity joint angles were estimated for each point of the gait cycle. Intraclass correlations were greater than 0.98 for all temporal distance metrics for both speeds. Lower body segment lengths had intraclass correlations above 0.90. Participant average joint angle waveforms displayed consistent patterns between visits. The average inter-trial and inter-session variability in joint angles across speeds were 1.17 and 1.45 degrees, respectively. The variability in joint angles between visits was less than typically reported for marker-based methods. Gait outcomes measured with Theia3D were highly repeatable in participant(s) with knee osteoarthritis providing further validation for its use in research assessment and longitudinal studies.

If you’re interested in more details about this study, check out the full online publication.

If you would like to download all validations on Theia3D, reach out to us here!

Recent Posts
Beyond The Radar Gun: How Dean Jackson uses Theia3D For Incremental Velocity Analysis
This article is a first in a miniseries that breaks down what motion capture can show beyond radar, ball data, and standard video. In this first installment, Dean breaks down how he uses Incremental Velocity Analysis, or IVA, to study what changes biomechanically as pitchers move closer and closer to max output.
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A 2025 study published in the Journal of Biomechanics compared shoulder kinematics measured with Theia3D markerless motion capture against gold-standard marker-based motion capture across full arm ranges of motion. The results show strong agreement for many movements, particularly in the coronal plane, while also highlighting where caution is still required, especially at the extremes of ranges of motion and in transverse-plane rotations.
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Baseball tracking systems can measure everything from ball flight and bat path to workload and full-body biomechanics, but each category answers a different question. This guide compares leading options and explains how to choose the right system based on what your program needs to measure, where it will operate, and whether it can connect athlete mechanics to baseball outcomes.
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Summary