Contactless Blood Oxygen Saturation Estimation from Facial Videos Using Deep Learning.

Blood oxygen saturation (SpO) is an essential physiological parameter for evaluating a person's health. While conventional SpO measurement devices like pulse oximeters require skin contact, advanced computer vision technology can enable remote SpO monitoring through a regular camera without skin contact. In this paper, we propose novel deep learning models to measure SpO remotely from facial videos and evaluate them using a public benchmark database, VIPL-HR.

Deep Learning Methods for Remote Heart Rate Measurement: A Review and Future Research Agenda.

Heart rate (HR) is one of the essential vital signs used to indicate the physiological health of the human body. While traditional HR monitors usually require contact with skin, remote photoplethysmography (rPPG) enables contactless HR monitoring by capturing subtle light changes of skin through a video camera. Given the vast potential of this technology in the future of digital healthcare, remote monitoring of physiological signals has gained significant traction in the research community.