Peripheral oxygen saturation measurement using an RGB camera

• Published in: IEEE sensors journal Vol. 23; no. 21; p. 1
• Main Authors: Wu, Bing-Jhang, Wu, Bing-Fei, Dong, You-Cheng, Lin, Hsiang-Chun, Li, Ping-Hung
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Altitude; Blood; blood oxygen saturation; Cameras; COVID-19; Estimation; Feasibility studies; health monitoring; High altitude; Hypoxemia; Optical filters; Oxygen; Oxygen content; peripheral oxygen saturation; remote healthcare; remote photoplethysmography; Sea measurements; Sensors; smart healthcare; SpO<sub xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">2
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2023.3284196

In 2019, the COVID-19 pandemic became a serious issue around the world. Low blood oxygen is the most important symptom of COVID-19. However, many patients have no obvious respiratory symptoms and exhibit silent hypoxemia, which is typically not noticed by patients but can cause severe damage. Hypoxemia is also related to high-altitude illness, highlighting the importance of detecting hypoxemia for travelers in high-altitude areas. The most commonly used device for monitoring blood oxygen remains difficult to access for the general population. To address this problem, a few camera-based methods have been proposed. Nevertheless, these approaches are generally not robust and have not been evaluated completely. Therefore, we conduct a pilot study to show the feasibility of camera-based SpO 2 estimation, and then propose a contact-free system by which to measure SpO 2 using a general RGB camera. We adopt a k-nearest neighbor model as the backbone algorithm. For a comprehensive evaluation, we compiled two SpO 2 datasets: one collected at an altitude of 3,150 meters, and the other collected at 102 meters above sea level. Sixty subjects participated in the experiments, which included a mobile phone, a webcam, and an industrial camera. In a leave-one-subject-out validation, the proposed method respectively yields a mean absolute error of 4.39%, 4.45%, and 4.22% using the three cameras. In general, the proposed approach outperforms the benchmark algorithms. To our best knowledge, this is the first work to utilize real high-attitude data to address camera-based SpO 2 measurement.