Does the device measure what it claims to measure?
Does the raw signal reflect the physiological quantity the device claims to capture.
The approach
One framework, three layers.
One framework runs across health and performance, because the failure modes (and the obligation to catch them) are the same. This is the logic, not the full methodology.
Are the outputs it derives from that signal valid?
Do the metrics computed from that signal actually hold.
Does it hold up inside the decisions it is meant to inform?
Does it work inside real clinical or performance practice, with the people who rely on it.
The framework is domain-agnostic. That is why a single engine serves clinical and high-performance work, from elite sport to defence.
Provenance
Layers 01 and 02 are the V3 framework (verification and analytical validation), the field's standard reference for whether a biometric monitoring technology is fit for purpose. We did not invent it and we use it because it is right. Layer 03 is our extension: V3 asks whether a metric tracks a meaningful clinical state, and we push that further into whether it survives the decision and the workflow it is built for, in high-performance settings as well as clinical ones.
Goldsack et al. (2020), Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs). npj Digital Medicine 3:55. doi:10.1038/s41746-020-0260-4 ↗
Want this run over your product?
The framework is what every engagement applies. The offerings, and what each one costs, are on the services page.