Abstract
In light of the recent Coronavirus disease (COVID-19) pandemic, peripheral oxygen saturation (SpO2) has shown to be amongst the vital signs most indicative of deterioration in persons with COVID-19. To allow for the continuous monitoring of SpO2, we attempted to demonstrate accurate SpO2 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 SpO2 from 20 subjects. The ratio of ratios (R) used in pulse oximetry to estimate SpO2 was robustly extracted from the red and infrared PPG signals during the breath-hold segments using novel feature extraction and PPGgreen-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 SpO2. The accurate SpO2 estimation provided by our custom biosensor and the algorithms provide research opportunities for a wide range of disease and wellness monitoring applications.
Highlights
Due to the novel Coronavirus disease (COVID-19) pandemic, there is a clear need to monitor respiratory functions in outpatient settings to help assess the progression of COVID-19 during the presymptomatic, symptomatic, and recovery stages
We were able to lower the mean root-mean-square error (RMSE) by 0.36% and increase Pearson correlation coefficient (PCC) by 0.02 when compared to the globalized model
AAccccoorrddiinnggttootthheerreessuullttss shown in Figure 8a, we found that increasing calibration duration from 1 s to 20 s while fixing SpO2 range to 30% leads to significant (p < 0.05) reduction in mean RMSE across the FOR PEER REVIEW
Summary
Due to the novel Coronavirus disease (COVID-19) pandemic, there is a clear need to monitor respiratory functions in outpatient settings to help assess the progression of COVID-19 during the presymptomatic, symptomatic, and recovery stages. In a recent effort to record and model the trajectories of several vital signs in hospitalized COVID-19 patients, Pimentel et al showed that peripheral oxygen saturation (SpO2) is amongst the most indicative of parameters of COVID-19 progression prior to primary outcomes, suggesting the importance to monitor SpO2 continuously [1]. Existing SpO2 measurement devices are inconvenient for monitoring in outpatient settings. SpO2 is measured through pulse oximeters placed at peripheral extremities such as the fingers; these devices obstruct normal activities of daily living (ADLs) due to restriction of finger usage. Commercial wrist-worn devices such as Apple Watch, Fitbit Sense Advanced Smartwatch, and Garmin Vivosmart 4 have been developed that allow for more convenient monitoring and offer continuous SpO2 measurements. Peripheral sites such as the wrist respond to apnea events at a slower than central sites [4,5] due to the redistribution of blood flow, oxygen conservation [6], and their distal location to the heart
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