Calibrating Oxygen Saturation Measurements for Different Skin Colors Using the Individual Typology Angle

Abstract

Since the start of the SARS-CoV-2 pandemic, wearable devices featuring oxygen-saturation measurements have gradually attracted public attention. The US Food and Drug Administration (FDA) has, however, raised doubts about the accuracy of watch-type oximeters (e.g., Apple Watch and Fitbit Sense) for darker-skinned users. That is, the accuracy of oxygen-saturation measurements is affected by skin tone. Accordingly, this article proposes a method of calibrating the bias of the oxygen-saturation measurement caused by differences in skin tone. We integrate a color sensor into a wearable device featuring the function of oxygen-saturation measurement. We also use the individual typology angle (ITA) to quantify the user's skin color and the skin's ITA quantization value to calibrate the oxygen saturation value of the pulse oximeter sensor. The oxygen-saturation-calibration algorithm of the ITA-quantified value is suitable for determining the R-value bias caused by skin color. Our experimental findings derive from testing the R-values of subjects with different skin colors and simulating and verifying oxygen saturation ranges from 70% to 100%. The findings suggest that it is possible for the oxygen saturation bias of darker-skinned subjects to be reduced from an Arms error of 5.44% to an Arms error of 0.82%; that is, using ITA-quantified value for calibration, the accuracy of oxygen saturation measurements (OSMs) has been significantly improved. The proposed method enables the oxygen-saturation measurements of dark-skinned subjects to comply with the FDA guidance and ISO 80601-2-61:2017 standards, meaning that this study's method can effectively improve the accuracy of the oxygen-saturation measurements of watch-type oximeters.