Identity spoofing is a contender for high-security face recognition applications. Nowadays, our images are wide-spread on the internet and can be potentially used to attack biometric systems. The latest developments in counter-measures for facial spoofing fail to recognize attacks in challenging conditions. Recent advances in the field of contactless cardiac heart rate measurement using commodity hardware opens up new possibilities for face biometrics anti-spoofing. Unfortunately, current research in commodity photoplethysmography (PPG) is not reproducible. Deployment for face recognition also requires addressing speed and illumination robustness. We propose to conduct a reproducible research study with a new public database to be collected, including user videos and related biomedical signals. We will develop baseline systems for the detection of heart rates based on current state of the art. We will leverage from in-house know-how in face detection, and tracking to design an open-source processing chain for commodity PPG applied to face biometrics anti-spoofing that can be used stand-alone or in parallel to existing counter-measures.