Remote photoplethysmography for health assessment: a review informed by IntelliProve technology

Remote photoplethysmography (rPPG) is a non-invasive method that accurately measures clinical biomarkers, including heart rate, respiration rate, heart rate variability, blood pressure and oxygen saturation. The contactless technique relies on standard cameras and ambient light, proving highly accessible and significant for the assessment of general health. Despite its potential, comprehensive research on rPPG applications for health assessment is scarce.

This review summarizes the current state of knowledge on rPPG health assessments, covering both fundamental physiological monitoring and higher-level health insights. The paper consults the rPPG-based HealthTech company, IntelliProve, as a real-world example to identify relevant outputs that are currently applied in everyday settings.

A literature review was performed to identify validated physiological biomarkers and emerging health metrics in rPPG research, using Google Scholar, PubMed and Scopus.

The search identified 96 relevant studies, of which 54 directly investigated rPPG-related technologies. The remaining papers provided theoretical context and complementary support relevant to rPPG-based health metrics. Similarly to IntelliProve's approach, several studies combined rPPG with additional inputs to enhance the accuracy of complex health assessments, such as sleep quality evaluation. The review identified well-established health outputs, including heart rate, respiratory rate, heart rate variability, hypertension risk and mental stress detection, as well as exploratory health metrics, including the assessment of mental health risk energy levels, sleep quality and resonant breathing state. To the author's knowledge, existing literature heavily focuses on basic vitals derivation, with limited research into rPPG's broader health applications.

This review synthesizes rPPG-based health applications, demonstrating strong evidence for fundamental physiological monitoring and an increasing interest in higher-level health metrics. Overall, this paper establishes the groundwork for continued research into the growing application of rPPG for health assessments.