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- W2904703014 abstract "Arterial oxygen saturation ([Formula: see text]) is an indicator of how much oxygen is carried by hemoglobin in the blood. Having enough oxygen is vital for the functioning of cells in the human body. Measurement of [Formula: see text] is typically estimated with a pulse oximeter, but recent works have investigated how smartphone cameras can be used to infer [Formula: see text]. In this paper, we propose methods for the measurement of [Formula: see text] with a smartphone using convolutional neural networks and preprocessing steps to better guard against motion artifacts. To evaluate this methodology, we conducted a breath-holding study involving 39 participants. We compare the results using two different mobile phones. We compare our model with the ratio-of-ratios model that is widely used in pulse oximeter applications, showing that our system has significantly lower mean absolute error (2.02%) than a medical pulse oximeter." @default.
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- W2904703014 date "2019-11-01" @default.
- W2904703014 modified "2023-09-29" @default.
- W2904703014 title "Measuring Oxygen Saturation With Smartphone Cameras Using Convolutional Neural Networks" @default.
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- W2904703014 doi "https://doi.org/10.1109/jbhi.2018.2887209" @default.
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