A combination of symptom and sensor data from wearable devices could enhance detection of COVID-19 positive and negative cases in symptomatic individuals, a new study shows (Quer et al. 2020).
Study authors, affiliated with the Scripps Research Translational Institute (USA), point out that "individual changes in physiological measures captured by most smartwatches and activity trackers are able to significantly improve the distinction between symptomatic individuals with and without a diagnosis of COVID-19 beyond symptoms alone".
Resting heart rate (RHR), physical activity and sleep are among the biometric measures assessed in this study on improving COVID-19 detection, which builds on an earlier retrospective analysis on the effectiveness of consumer sensors to identify individuals with influenza-like illness.
In their previous study, the Scripps team created a prospective app-based research platform called DETECT (Digital Engagement and Tracking for Early Control and Treatment). This platform enables individuals to share their sensor data, self-reported symptoms, diagnoses and electronic health record data. As such, DETECT can facilitate identification and tracking of viral illnesses, including COVID-19, at the individual and population levels.
- Making Telemedicine more Human
- Google Cloud unveils AI tools to help healthcare analyze unstructured medical text
- AMA Unveils 2 Vaccine-Specific CPT Codes for Coronavirus Immunizations
- Remote Patient Monitoring Innovation Challenge Showcase by Adaptation Health
- Machine Learning to Predict Efficacy of Anti-Cancer Drug