Resting Heart Rate as a Digital Biomarker

Resting heart rate is the number of heartbeats per minute when a person is awake, at rest and not recently exerted. Measured once in clinic it reflects a single moment, including the effect of having travelled to the appointment. Measured continuously by a wearable it becomes something different: a stable personal parameter with a known day to day variability, against which deviation can be detected.

Elevated resting heart rate is independently associated with all cause and cardiovascular mortality across large cohorts, an association that persists after adjustment for fitness and conventional risk factors. It is also one of the few measures where the wearable version has been characterised in very large datasets, which has established how much a normal person's resting heart rate varies with age, sex, sleep, body mass index and season.

Wearables estimate heart rate optically, using photoplethysmography to detect the pulsatile change in light absorption as blood volume changes with each beat. At rest and during sleep this agrees closely with chest strap electrocardiography, which is the practical reference standard. Accuracy degrades during vigorous or irregular movement, which is why resting values are the most dependable output these devices produce.

Devices differ in how they define the resting value. Some report the lowest sustained rate during sleep, some a trimmed average of quiet waking periods, and some an overnight minimum. Those definitions produce different numbers from the same physiology, so a study should record the device and its firmware version and should avoid pooling resting heart rate across device types.

Resting heart rate is collected in almost every wearable study, sometimes as the focus and more often as context needed to interpret activity data. As a research measure in its own right it is used for prognostic stratification, for detecting physiological response to training or rehabilitation, and for early detection of infection, where a rise typically appears before symptoms.

In cardiology it is used to assess rate control and the effect of rate limiting medication. Because it has no direct questionnaire counterpart, it is normally reported alongside a functional classification such as the New York Heart Association class or the Duke Activity Status Index, which describe the burden the measure is being used to track rather than measuring the same construct.

Resting heart rate responds to a great deal besides cardiac status, including fitness, medication, caffeine, alcohol, illness, stress, dehydration and ambient temperature. A change in the value is a prompt to look for a cause rather than a finding in itself.

Optical estimation is less accurate in irregular rhythms, in people with poor peripheral perfusion, and under some sensor and skin tone combinations. Cross device comparison is unreliable because devices define the resting value differently. The measure is best used within a person over time and is weakest as an absolute number compared against a population norm.

• Jensen MT, et al. Elevated resting heart rate, physical fitness and all-cause mortality: a 16-year follow-up in the Copenhagen Male Study. Heart. 2013. pubmed.ncbi.nlm.nih.gov
• Zhang D, et al. Resting heart rate and all-cause and cardiovascular mortality in the general population: a meta-analysis. CMAJ. 2016. pubmed.ncbi.nlm.nih.gov
• Quer G, et al. Inter- and intraindividual variability in daily resting heart rate and its associations with age, sex, sleep, BMI, and time of year. PLoS One. 2020. pubmed.ncbi.nlm.nih.gov
• Nanchen D. Resting heart rate: what is normal? Heart. 2018. pubmed.ncbi.nlm.nih.gov