Video-Assisted Clinical Care for Remote Management of COVID-19

Due to the COVID-19 pandemic, the need for biomedical monitoring devices has increased for collecting vital signs from patients virtually. This paper will discuss developing an iOS mobile application that will ingest video frames in real-time to provide oxygen saturation and heart rate values. We provide two techniques for capturing data using 1) face monitoring under natural light and 2) fingertip monitoring using the iPhone's flashlight. We observed an average Root Mean Squared Error (RMSE) of 3.6 for heart rate estimation using fingertip recordings and 13.25 using face recordings. For oxygen saturation, we obtained the RMSE for each class between SpO2 values 94 - 99%. The lowest RMSE provided from our application was 0.26 for fingertip recording and 0.22 for face recording at SpO2 level 96%. The highest RMSE was 6.34 for fingertip recording and 6.56 for face recording at SpO2 level 99%. These preliminary models will be further enhanced through a clinical study with UC Davis Health as we collect data from participants with respiratory diseases.