The Validity Check Every Biomechanics Lab Should Be Running

Summary

In this series, we're unpacking the STRN Quality Framework — a set of 25 measurable features across 5 pillars for evaluating motion capture systems. This post covers Pillar B: Validity, examining the evidence base supporting Theia3D's measurement accuracy across diverse research populations.

Evaluating Established Benefit with the STRN Quality Framework

When you’re investing in motion capture technology — whether for a research lab, applied biomechanics setting, or field environment — specs alone don't tell the full story. The real question is: Does the system work, in ways that actually matter?

That's the focus of Pillar B: Established Benefit in the Sports Technology Research Network (STRN) Quality Framework. It’s about proven, validated value — not just theoretical performance.

What Does “Established Benefit” Actually Mean?

Pillar B evaluates whether a motion capture system: measures what it claims to (construct validity), matches known gold standards (concurrent validity), supports predictive insights over time (predictive validity), and functions reliably in real-world settings (functionality).

Construct Validity

Theia3D has been independently validated across a wide range of biomechanical constructs including spatiotemporal gait parameters, joint angles and moments, balance-related quantities, upper extremity motor function, and running metrics and ground reaction force estimates.

Beyond matching known values, Theia3D has also shown promise in discriminating between research groups, including research participants with knee osteoarthritis vs. healthy controls, children with cerebral palsy vs. typically developing peers, and individual gait characteristics vs. normative baselines.

Concurrent Validity

Theia3D has demonstrated strong alignment with previously validated systems for metrics including lower limb alignment, center of mass and whole-body angular momentum, joint reaction forces via musculoskeletal modeling, gait pathology indices, and muscle activation timing.

Predictive Validity

Early studies using kinematic data from systems like Theia3D have shown promise in identifying fall risk in older adults, estimating injury likelihood in runners, and tracking movement trends in industrial workers. Theia3D’s automated, scalable data capture enables long-term population studies — a foundational step in building predictive models.

Functionality

Theia3D is designed for real-world usability. No markers. No manual labeling. Just calibrated video and the flexibility to run with your existing camera setup. It uses standard video input and supports multiple third-party camera systems.

Recent Posts

Theia3D Apex - The Next Generation of Markerless Motion Capture Has Arrived

After much anticipation, Theia3D Apex is now available for all users. This release represents a significant update to our markerless tracking models and introduces our new baseball ball tracking add-on feature, along with other enhancements and updates. In this overview, we’ll discuss what you can expect after updating to Theia3D Apex, including the improvements offered by our new tracking models, a look at how our ball tracking feature was validated, and other new software features.

A Major Research Milestone for Theia3D

More than 50 independent, peer-reviewed research publications now cite, evaluate or review Theia3D across domains including gait, sports performance, postural control, upper-extremity movement and other biomechanics applications. These publications are available in world-leading journals including Journal of Biomechanics, Journal of Applied Biomechanics, Gait & Posture and Clinical Biomechanics. Together, they represent a growing body of evidence across different movements, populations and environments, reinforcing Theia3D’s position as the most extensively validated markerless motion capture system.

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.