A transparent validation roadmap often creates more confidence than a vague claim that the technology is accurate under all conditions. Here is what we test, how we test it, and what we report.
Every claimed capability has a defined validation study. We do not present results that have not been tested.
Validation reports include rejection rates, edge case failures, and conditions where accuracy degrades.
Camera-measured values (HR, RR) are validated separately from calculated references (BMI, REE).
Validation scope is explicit. Results outside tested conditions are not claimed.
Known-frequency synthetic signals injected into the pipeline. Validates that the rPPG algorithm extracts the correct frequency under ideal conditions.
Pre-recorded videos with known ground truth, captured in stable lab conditions. Tests the pipeline against real camera data without confounding real-world variables.
Simultaneous Camera Vital Check scan and validated reference device measurement. Direct comparison of HR and RR values.
Real users, real hardware, real environments. Measures valid scan rate, rejected scan rate, and rescan patterns.
Performance across skin tones, lighting conditions, devices, and demographics. Identifies systematic bias or accuracy variation.