Smartphone-based SpO₂ measurement by exploiting wavelengths separation and chromophore compensation

Patients with respiratory diseases require frequent and accurate blood oxygen level monitoring. Existing techniques, however, either need a dedicated hardware or fail to predict lowsaturation levels. To fill in this gap,we propose a phone-based oxygen level estimation system, called PhO₂, using camera and flashlight functions that are readily available on today's off-the-shelf smartphones. Since the phone's camera and flashlight were not made for this purpose, utilizing them for oxygen level estimation poses many difficulties. We introduce a cost-effective add-on together with a set of algorithms for spatial and spectral optical signal modulation to amplify the optical signal of interest while minimizing noise. A near-field-based pressure detection and feedback mechanism are also proposed to mitigate the negative impacts of user's behavior during the measurement. We also derive a non-linear referencing model with an outlier removal technique that allows PhO₂ to accurately estimate the oxygen level from color intensity ratios produced by the smartphone's camera. An evaluation on COTS smartphone with six subjects shows that PhO₂ can estimate the oxygen saturation within 3.5% error rate comparing to FDA-approved gold standard pulse oximetry. In addition, our evaluation in hospitals presents high correlation with ground-truth qualified by the 0.83/1.0 Kendall τ coefficient.