Journal article Open Access
The COVID-19 pandemic has led more people to start using wearable technology to track vital signs, physical activity, and sleep. The significant features of these devices include their capability to collect continuous, noninvasive data. We developed a COVID-19 risk stratification model using the Biostrap wearable device which utilizes a baseline-adjusted continuous scale and other escalation points-based on our recent case report, to enhance the National Early Warning Score (NEWS2). Preliminary research has found that our adjusted Early Warning Score (Biostrap-EWS) might be highly specific in identifying early-stage respiratory infections. We present the case of Biostrap CEO Sameer Sontakey, a 35-year-old man, whom the app notified as having a high likelihood of respiratory illness after which the diagnosis SARS-CoV-2 was confirmed with a nasal swab. Our Biostrap-EWS algorithm appears to detect respiratory infections in a real-world environment via passively collected biometric data. To validate the reliability of the algorithm, further research is required.
A 35-year-old CEO who detected COVID-19 with his wearable biosensor.pdf
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