Robust Pulse Rate From Chrominance-Based rPPG

TLDR

Remote photoplethysmography enables contactless monitoring of blood volume pulse, yet prior motion‑robustness efforts using RGB blind source separation have shown limited success. The study analyzes motion artifacts to demonstrate that chrominance‑based rPPG methods are far superior. The authors analyze motion artifacts and develop chrominance‑based rPPG algorithms that outperform RGB blind source separation. In 117 stationary subjects, the chrominance‑based method achieved 92 % agreement with contact PPG (±1.96σ) and halved RMSE and SD compared to BSS, while in a fitness setting it raised correct pulse‑rate detection from 79 % to 98 % for moderate motion and from <11 % to >48 % for vigorous motion, indicating that the enhanced robustness could broaden the technology’s application scope.

Abstract

Remote photoplethysmography (rPPG) enables contactless monitoring of the blood volume pulse using a regular camera. Recent research focused on improved motion robustness, but the proposed blind source separation techniques (BSS) in RGB color space show limited success. We present an analysis of the motion problem, from which far superior chrominance-based methods emerge. For a population of 117 stationary subjects, we show our methods to perform in 92% good agreement ( ±1.96σ) with contact PPG, with RMSE and standard deviation both a factor of 2 better than BSS-based methods. In a fitness setting using a simple spectral peak detector, the obtained pulse-rate for modest motion (bike) improves from 79% to 98% correct, and for vigorous motion (stepping) from less than 11% to more than 48% correct. We expect the greatly improved robustness to considerably widen the application scope of the technology.