Wear-time / data coverage

FAQ

What is wear-time / data coverage?

Coverage is usable recorded hours divided by the hours the protocol prescribed the subject to wear the device, usually shown as a percent. Gap hours are prescribed minus usable. “Usable” must match the statistical analysis plan (for example after artifact rejection).

Why do biosensor and RPM studies care about coverage?

Primary endpoints often assume a minimum fraction of valid data. Low coverage can bias exposure estimates, trigger protocol deviations or make a subject non-evaluable. Sponsors typically pre-specify a coverage threshold for analysis sets.

How should I define usable hours?

Define usable the same way in the protocol, device DFU and SAP: which signal-quality flags count, whether charging gaps count as non-wear, and how partial hours are rounded. Changing the definition after database lock undermines the endpoint.

Is a 70% threshold required by FDA?

No universal FDA percentage applies to every wearable. Seventy percent is only this form’s default example. Choose a threshold justified by the clinical question, prior data and labeling claims, and document it before unblinding.

How does coverage relate to battery life and form factor?

Short battery life, poor adhesion and uncomfortable form factors drive non-wear and gaps. Pair coverage planning with battery-life estimates and human-factors observations rather than treating missingness as purely statistical.

Does this tool store subject-level wear logs?

No. It only computes coverage from the three numbers you enter. Subject-level logs belong in your EDC or data lake under your privacy controls.