A Proposed Brazilian Dataset and Approach for Remote Blood Oxygen Saturation Measurement from Facial Videos
Resumo
Blood oxygen saturation (SpO2) measurement is one of the most commonly used vital signs in the clinical assessment of patients. Typically, this measurement is performed using pulse oximeters, which, although accurate, present certain limitations, as they rely on direct skin contact and are sensitive to external factors. To overcome these constraints, there has been growing interest in remote monitoring of vital signs through imaging. In this work, the creation of a Brazilian dataset for SpO2 estimation is proposed, focusing on the diversity of skin tones, ages, and medical conditions. The recorded videos will be synchronized with SpO2 values obtained from pulse oximeters. Subsequently, the recordings will be converted into Spatial-Temporal Maps (STMaps), which compact spatial and temporal information, and a 2D convolutional neural network will be used to predict SpO2 values from these representations.This dataset and reference model aim to support research in non-invasive remote monitoring of vital signs, providing an inclusive framework for future studies and improving the reliability of SpO2 estimation across different populations.
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