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Wearable Devices Detect Physiological Changes that Precede and Are Associated with Symptomatic and Inflammatory
Pragya Sharma1, Matteo Danieletto1,2, Jessica K Whang3
1Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Medrxiv : the Preprint Server for Health Sciences
|October 3, 2025
Summary
Wearable devices can detect physiological changes preceding rheumatoid arthritis (RA) flares. Monitoring heart rate and steps may help predict symptomatic and inflammatory RA flare development.
Area of Science:
- Rheumatology
- Biomedical Engineering
- Digital Health
Background:
- Rheumatoid arthritis (RA) is characterized by physiological alterations.
- Current monitoring methods for RA flares can be reactive.
Purpose of the Study:
- To investigate if wearable device data can identify and predict rheumatoid arthritis (RA) flares.
- To assess physiological metric changes before symptomatic and inflammatory flares.
Main Methods:
- 53 RA participants used wearable devices (Apple Watch, Fitbit, Oura Ring) for a mean of 105 days.
- Collected data included heart rate (HR), resting heart rate (RHR), heart rate variability (HRV), and steps.
- Statistical models analyzed associations between physiological metrics and RA flare/remission periods.
Main Results:
- Lower steps and higher nighttime HR were observed during symptomatic periods.
- Higher daily HR, daytime HR, nighttime HR, and RHR correlated with inflammatory flares.
- Circadian HRV features distinguished flares from remission.
- All monitored metrics showed alterations up to 4 weeks before flares.
Conclusions:
- Wearable device data show potential for monitoring RA disease activity.
- Physiological metrics from wearables may predict symptomatic and inflammatory RA flares.
- This technology could enable proactive RA management and intervention.
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