Remote photoplethysmography (rPPG) to measure heart rate and blood oxygenation levels using colour, infrared and depth data from real home environments

  • Pireh Pirzada

Student thesis: Doctoral Thesis (PhD)


Heart Rate (HR) and Blood Oxygenation Level (SPO2) are physiological signs that are critically important measurements in the assessment of emergent ill-health. These typically require physical contact and blood tests that are often prohibitive for people with certain incapacities, severe illnesses, or burns. Currently, there is no commercially available system for measuring HR and SPO2 simultaneously remotely, such as through Remote Photoplethysmography (rPPG). Furthermore, there is a gap in the literature on rPPG research as it is unclear which preprocessing techniques and noise reduction algorithms work best in a realistic scenario encompassing diverse demographic characteristics.

This thesis addresses these gaps by answering the question ‘How can rPPG be used for unobtrusively measuring vital signs for diverse participants in uncontrolled (home) environments with a low Root Mean Square Error (RMSE)?”. The Automated Remote Pulse Oximetry System incorporates Red, Green, Blue, Depth and Infrared (IR) data to measure HR and SPO2 remotely from Regions of Interest (ROIs) from the face. Various preprocessing and noise reduction algorithms for measuring vital signs have been evaluated across different skin pigmentation types using multispectral imaging of participants’ faces over time. This novel approach uses the frequency content to obtain the HR and a depth-calibrated ratiometric measurement from Red and IR to measure SPO2. Additionally, this research with 40 participants identifies and reports factors from real-life environments that impact the system’s error rate. Detrending, interpolating, hamming, and normalising the signal using a 15-second temporal window size with FastICA produced the lowest RMSE of 7.8 for HR with an r-correlation value of 0.85 and RMSE of 2.5 for SPO2 across different skin pigmentation types which also has the lowest computation time of 1.75ms per measurement. This rPPG system has the potential for deployment in uncontrolled environments offering widespread benefits for those who require remote HR and SPO2 measurement.
Date of Award28 Nov 2023
Original languageEnglish
Awarding Institution
  • University of St Andrews
SupervisorDavid Cameron Christopher Harris-Birtill (Supervisor) & Gayle Helane Doherty (Supervisor)


  • rPPG
  • Heart rate
  • Blood oxygenation
  • Signal processing
  • Computer vision
  • Kinect V2
  • Remote studies
  • Remote measurement

Access Status

  • Full text embargoed until
  • 4 October 2025

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