Consumer-grade wearables identify changes in multiple physiological systems during COVID-19 disease progression

Area of Science:

• Biomedical Engineering
• Digital Health
• Wearable Technology

Background:

• Real-time patient monitoring is crucial for disease tracking, particularly during pandemics.
• Consumer-grade wearables offer a scalable solution for continuous physiological data collection.

Purpose of the Study:

• To investigate the utility of decomposing heart rate signals from low-cost wearables for multidimensional physiological descriptions of COVID-19 infection.
• To identify specific heart rate features that can differentiate between symptomatic and healthy periods.

Main Methods:

• Decomposition of heart rate data from consumer wearables into distinct physiological signals.
• Analysis of basal heart rate, heart rate response to physical activity, circadian heart rate variation, and heart rate autocorrelation.
• Classification of symptomatic versus healthy periods based on altered physiological features.

Main Results:

• Significant alterations in basal heart rate, heart rate response to activity, circadian variation, and autocorrelation were observed during COVID-19 infection.
• Increased heart rate and autocorrelation were associated with symptom onset.
• Heart rate response to activity increased post-symptom onset, particularly in individuals with cough.
• Circadian heart rate variation showed a blunting effect at symptom onset.

Conclusions:

• Decomposing heart rate from wearables provides a multidimensional view of physiological changes during COVID-19.
• Specific heart rate features are sensitive indicators of infection and disease progression.
• This approach enables innovative remote disease monitoring using accessible consumer technology.