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Updated: Jul 21, 2025

An Application for Pairing with Wearable Devices to Monitor Personal Health Status
Published on: February 3, 2022
Pulse oximetry values from 33,080 participants in the Apple Heart & Movement Study
Ian Shapiro1, Jeff Stein1, Calum MacRae2,3
1Apple Inc., Cupertino, CA, USA.
Wearable pulse oximetry (SpO2) devices captured 72 million readings from over 33,000 people. Analysis revealed healthy circadian oxygen saturation patterns and identified demographic variations in SpO2 trends.
Area of Science:
- Physiology
- Biomedical Engineering
- Digital Health
Background:
- Wearable devices offer novel opportunities for large-scale physiological data collection.
- Pulse oximetry (SpO2) measurements can be obtained non-invasively.
- Understanding SpO2 variations in diverse populations is crucial for establishing health benchmarks.
Purpose of the Study:
- To analyze a large dataset of SpO2 measurements from wearable devices.
- To establish population-level reference trends for SpO2 under naturalistic conditions.
- To investigate demographic influences on SpO2 circadian patterns and trends.
Main Methods:
- Cross-sectional analysis of 72 million SpO2 values from 33,080 participants in the Apple Heart and Movement Study.
- Stratification by age, sex, BMI, home altitude, and race/ethnicity.
- Multivariate ordinary least squares regression to quantify population-level trends.
Main Results:
- SpO2 measurements exhibited consistent circadian patterns across all demographic groups, with lower saturation overnight.
- Daytime SpO2 regression coefficients aligned with laboratory-based reference models.
- Significant differences in age- and BMI-dependent SpO2 trends were observed between sexes.
- Small, statistically significant differences in daytime SpO2 were noted among racial/ethnic groups.
Conclusions:
- Wearable SpO2 devices can establish healthy population reference trends outside clinical settings.
- Circadian SpO2 patterns are robust across demographics, but age, sex, and BMI influence trends.
- Further research can refine SpO2 interpretation based on individual demographic factors.
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