| Summary: | In light of the recent Coronavirus disease (COVID-19) pandemic, peripheral oxygen saturation (SpO<sub>2</sub>) has shown to be amongst the vital signs most indicative of deterioration in persons with COVID-19. To allow for the continuous monitoring of SpO<sub>2</sub>, we attempted to demonstrate accurate SpO<sub>2</sub> estimation using our custom chest-based wearable patch biosensor, capable of measuring electrocardiogram (ECG) and photoplethysmogram (PPG) signals with high fidelity. Through a breath-hold protocol, we collected physiological data with a wide dynamic range of SpO<sub>2</sub> from 20 subjects. The ratio of ratios (R) used in pulse oximetry to estimate SpO<sub>2</sub> was robustly extracted from the red and infrared PPG signals during the breath-hold segments using novel feature extraction and PPG<sub>green</sub>-based outlier rejection algorithms. Through subject independent training, we achieved a low root-mean-square error (RMSE) of 2.64 ± 1.14% and a Pearson correlation coefficient (PCC) of 0.89. With subject-specific calibration, we further reduced the RMSE to 2.27 ± 0.76% and increased the PCC to 0.91. In addition, we showed that calibration is more efficiently accomplished by standardizing and focusing on the duration of breath-hold rather than the resulting range in SpO<sub>2</sub>. The accurate SpO<sub>2</sub> estimation provided by our custom biosensor and the algorithms provide research opportunities for a wide range of disease and wellness monitoring applications.
|
|---|