Cited by 241Non-Invasive Vital Sign MonitoringHeart Rate Variability and Autonomic ControlPhysical Activity and Health

The DOI matches its Crossref record; 79 of the 79 references it cites were found in a registry or an index; 3 of the 99 sources its claims cite were checked for support.

Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research

Open access
Nelson, Benjamin W., Low, Carissa A., Jacobson, Nicholas, Areán, Patricia, Torous, John, Allen, Nicholas B.·2020·npj Digital Medicine

Abstract

Researchers have increasingly begun to use consumer wearables or wrist-worn smartwatches and fitness monitors for measurement of cardiovascular psychophysiological processes related to mental and physical health outcomes. These devices have strong appeal because they allow for continuous, scalable, unobtrusive, and ecologically valid data collection of cardiac activity in “big data” studies. However, replicability and reproducibility may be hampered moving forward due to the lack of standardization of data collection and processing procedures, and inconsistent reporting of technological factors (e.g., device type, firmware versions, and sampling rate), biobehavioral variables (e.g., body mass index, wrist dominance and circumference), and participant demographic characteristics, such as skin tone, that may influence heart rate measurement. These limitations introduce unnecessary noise into measurement, which can cloud interpretation and generalizability of findings. This paper provides a brief overview of research using commercial wearable devices to measure heart rate, reviews literature on device accuracy, and outlines the challenges that non-standardized reporting pose for the field. We also discuss study design, technological, biobehavioral, and demographic factors that can impact the accuracy of the passive sensing of heart rate measurements, and provide guidelines and corresponding checklist handouts for future study data collection and design, data cleaning and processing, analysis, and reporting that may help ameliorate some of these barriers and inconsistencies in the literature.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This paper reviews the use of wrist-worn consumer wearables for heart rate measurement in biobehavioral research and argues that lack of standardized data collection, processing, and reporting threatens reproducibility and generalizability. It provides two reporting checklists covering study design, technological factors, participant characteristics, data cleaning, analysis, and transparency.

Key findings

  • Wearables using photoplethysmography (PPG) can provide acceptable heart rate accuracy for research, especially with aggregated data and outlier removal, but not for medical settings; devices slightly underestimate absolute HR versus ECG by −0.9 to −7.2 bpm, with Apple Watch at −1.3 bpm and Fitbit at −9.3 bpm.
  • Error ranges were 1.20–6.70% for Apple Watch models and 2.38–21.36% for Fitbit models; any single real-time HR observation can deviate substantially from ECG, even when summary statistics are accurate.
  • Between 2008 and 2018, there was a 580% increase in articles containing “wearable” and “heart rate.”
  • Accuracy is influenced by motion artifacts and activity, with absolute error during activity reported as 30% higher than at rest; darker skin tone and tattoos can reduce green-light PPG accuracy, and larger wrist circumference or higher BMI are associated with reduced accuracy in some but not all studies.

Methods

  • Narrative review and guideline paper; no primary data collection, systematic review, or meta-analysis is described.
  • Synthesizes literature on commercial wrist-worn wearable HR accuracy and factors affecting measurement, focusing mainly on Apple Watch and Fitbit while noting Garmin, Samsung, and Microsoft.
  • Proposes two checklists (Tables 2 and 3) for descriptive reporting and potential covariates, and recommends open science practices such as preregistration, open code, and open data.

Limitations

  • The paper states that the field lacks metadata standards and consistent reporting of device type, firmware, sampling rate, biobehavioral variables, and demographic characteristics, which introduces noise and limits reproducibility and generalizability.
  • It states that accuracy evidence is mixed for activity intensity, skin tone, BMI, and wrist circumference, and that proprietary algorithms and lack of raw data prevent standardized processing.
  • Evident from the text: this is a narrative review without a systematic search or meta-analysis, and the proposed checklists are not empirically validated in the paper.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1038/s41746-020-0297-4

Cites

79 of 79 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

50 Not checked yet · 26 Own interpretation · 14 No basis given · 2 Supported · 1 Partly supported · accuracy not yet measured

Verify all 96 references — free account

Show all 33 claims

  • It may state two separate claims as one. 38
  • Probably not a substantial claim. 33
60 of 60
  • The paper relies on this without support.

    There is currently a lack of transparency from manufacturers on underlying algorithms and raw data outputs are often not provided.

    “Unfortunately, there is currently a lack of transparency from manufacturers on underlying algorithms and raw data outputs are often times not provided, which prevents researchers from dealing with this issue and creating a standardized protocol for transforming raw data to HR.”
  • The paper relies on this without support.

    The vast majority of wrist-worn wearable studies incorporating heart rate measurements do not report or control for participant race and ethnicity.

    “Currently, the vast majority of wrist-worn wearable studies incorporating HR measurements do not report or control for participant race and ethnicity, which undermines the ability to look at potentially important group differences in health outcomes and therefore decreases the ability of results to generalize to large segments of the population.”
  • The paper relies on this without support.

    Various wearable devices and versions on the market may use different hardware, which may introduce differences in heart rate recordings.

    “there are currently various wearable devices and versions on the market that have the potential to use different hardware, which may introduce differences in HR recordings.”
  • The paper relies on this without support.

    Wearable algorithms may be altered with firmware updates.

    “These algorithms, while often simplistic, may be altered with firmware updates”
  • The paper relies on this without support.

    Most studies fail to report firmware information.

    “yet most studies fail to report firmware information.”
  • The paper relies on this without support.

    Consumer wearables allow continuous, scalable, unobtrusive, big data collection of cardiac activity in real-world conditions with large samples.

    “The recent introduction of consumer wearables or wrist-worn smartwatches and fitness monitors for the digital measurement of cardiovascular health and psychophysiological stress has allowed for the continuous, scalable, and unobtrusive, “big data” collection of overall cardiac activity in real-world conditions with large samples that allow for the collection of passive, large-scale, and ecolog”
  • The paper relies on this without support.

    PPG technology can be used to index blood pressure, oxygen saturation, and cardiac output.

    “It is important to note that PPG technology can be used to index blood pressure, oxygen saturation, and cardiac output, which will likely be slowly rolled out into wearable technology moving forward.”
  • The paper relies on this without support.

    PPG can index heart rate variability, which is derived from beat-to-beat interval calculations in the time-domain.

    “In addition, PPG can index HRV, which is derived from beat to beat intervals calculations in the time-domain, such as root mean squared of successive differences or the standard deviation of NN intervals, the latter of which is used in the Apple Watch, but only with sporadic recordings throughout the day.”
  • The paper relies on this without support.

    Many commercial wearables do not provide beat-to-beat interval data to users.

    “Currently, many commercial wearables do not provide beat to beat interval data to users”
  • The paper relies on this without support.

    Research is heavily context dependent.

    “We do this because research is heavily context dependent.”
10 of 10

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Citations

Cites

Research works printed but not linked: 1

  1. Latvala, A. et al. Association of resting heart rate and blood pressure in late adolescence with subsequent mental disorders. JAMA Psychiatry 41, 89–104 (2016).

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Metadata

Authors
Nelson, B. W., Low, C. A., Jacobson, N., Areán, P., Torous, J., & Allen, N. B.
Affiliations
  • University of Oregon (US)
  • University of Pittsburgh (US)
  • Dartmouth College (US)
  • University of Washington (US)
  • Beth Israel Deaconess Medical Center (US)
Corresponding author
Nelson, Benjamin W.
Venue
npj Digital Medicine
Published
2020-06-26
Volume
3
Issue
1
Pages
90-90
ISSN
2398-6352 (ISSN-L)
OpenAlex
W3037389028
Cited by
241
References
78
Citations by year
2026: 22 · 2025: 30 · 2024: 54 · 2023: 46 · 2022: 39 · 2021: 42 · 2020: 7
FWCI
2.80
Type
journal article
Language
en
Open access
Locations
  • npj Digital Medicine (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Minerva Access (University of Melbourne) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Cancer Institute (K07CA204380)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
Keywords
heart rate measurement, consumer wearable devices, smartwatches, wrist-worn sensors, measurement accuracy, device standardization, reporting guidelines, skin tone, sampling frequency, reproducibility

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