EZCap
Effortless Motion Capture in Three Clicks

It estimates body keypoints from standard video without reflective markers or multi-camera lab hardware. EZCap uses AI models to convert that video into biomechanical features.

No. EZCap improves accessibility and scale for many use cases, but high-precision volumetric biomechanics still favors dedicated multi-camera laboratory setups.

Repeated functional assessment, remote follow-up, and trend monitoring over time when setup is standardized between sessions.

Accuracy varies with camera angle, movement plane, lighting, clothing, and occlusion. In-plane movements are generally more robust than out-of-plane rotations.

Small setup changes in distance, height, framing, speed, and subject orientation can change keypoint estimates. Use the same protocol each session.

In most practical workflows, trends over time are more reliable than one-off absolute values, unless setup conditions are tightly controlled.

Use a stable mount, keep full body regions of interest visible, align camera to the main movement plane, and avoid hand-held recording.

A lot. Even lighting and fitted clothing usually improve tracking confidence. Backlighting, shadows, and loose garments can degrade measurements.

Yes. Canes, walkers, braces, or limb overlap may obscure landmarks and lower confidence. Document these conditions and compare like-for-like sessions.

Typically 2 to 3 clean trials per task. If variability is high, collect more and use confidence-based filtering before interpretation.

Yes. Remote use is a key strength, but data quality depends on clear participant setup guidance and repeatable test conditions.

No. It is a decision-support tool and should be interpreted alongside history, examination, and established clinical measures.

Follow your organization policies for consent, retention, storage location, access controls, and compliance workflows. Governance is deployment-specific.