Peripheral oxygen saturation measurement using an RGB camera - Wu, Bing-Jhang; Wu, Bing-Fei; Dong, You-Cheng; Lin, Hsiang-Chun; Li, Ping-Hung (IEEE sensors journal, 2023)
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.