BioVerify is a deepfake detection approach that verifies facial video using remote photoplethysmography rather than visual artifacts. The method estimates blood volume pulse signals from facial skin regions, applies motion aware stabilization and a signal quality gate, then scores authenticity using physiological consistency constraints including periodicity, harmonic structure, inter window stability, and cross region coherence. This design aims to remain reliable under generator shift by testing for capture time biological dynamics that are difficult to synthesize consistently. The paper includes a formal signal model, an inference algorithm, an evaluation protocol, and measured results across manipulation families, ablations, and stress conditions relevant to identity verification and media authenticity workflows.