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. 2019 Jun 25;2:58.
doi: 10.1038/s41746-019-0134-9. eCollection 2019.

Real-world Heart Rate Norms in the Health eHeart Study

Free PMC article

Real-world Heart Rate Norms in the Health eHeart Study

Robert Avram et al. NPJ Digit Med. .
Free PMC article


Emerging technology allows patients to measure and record their heart rate (HR) remotely by photoplethysmography (PPG) using smart devices like smartphones. However, the validity and expected distribution of such measurements are unclear, making it difficult for physicians to help patients interpret real-world, remote and on-demand HR measurements. Our goal was to validate HR-PPG, measured using a smartphone app, against HR-electrocardiogram (ECG) measurements and describe out-of-clinic, real-world, HR-PPG values according to age, demographics, body mass index, physical activity level, and disease. To validate the measurements, we obtained simultaneous HR-PPG and HR-ECG in 50 consecutive patients at our cardiology clinic. We then used data from participants enrolled in the Health eHeart cohort between 1 April 2014 and 30 April 2018 to derive real-world norms of HR-PPG according to demographics and medical conditions. HR-PPG and HR-ECG were highly correlated (Intraclass correlation = 0.90). A total of 66,788 Health eHeart Study participants contributed 3,144,332 HR-PPG measurements. The mean real-world HR was 79.1 bpm ± 14.5. The 95th percentile of real-world HR was ≤110 in individuals aged 18-45, ≤100 in those aged 45-60 and ≤95 bpm in individuals older than 60 years old. In multivariable linear regression, the number of medical conditions, female gender, increasing body mass index, and being Hispanic was associated with an increased HR, whereas increasing age was associated with a reduced HR. Our study provides the largest real-world norms for remotely obtained, real-world HR according to various strata and they may help physicians interpret and engage with patients presenting such data.

Keywords: Epidemiology; Predictive markers.

Conflict of interest statement

Competing interestsG.M. has received research funding from Medtronic and Cardiogram Inc, is a consultant for Lifewatch and InCarda, and holds equity in InCarda. P.K. is an employee of Azumio. There are no disclosures for the remaining authors. Azumio provided no financial support for this study and only provided access to the heart rate data. Data analysis and interpretation was performed independently from Azumio.


Fig. 1
Fig. 1
Percentile graph of average real-world HR-PPG. a Percentile graph of average real-world HR-PPG according to the age. b Percentile graph of average real-world HR-PPG according to the gender c Percentile graph of average real-world HR-PPG according to the step counts

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