Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort

Anna Shcherbina, C. Mikael Mattsson, Daryl Waggott, Heidi Salisbury, Jeffrey W. Christle, Trevor Hastie, Matthew T. Wheeler, Euan A. Ashley
doi: https://doi.org/10.1101/094862
Anna Shcherbina
eDepartment of Biomedical Data Science, Stanford University, Stanford, CA USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
C. Mikael Mattsson
aDivision of Cardiovascular Medicine, Department of Medicine, Stanford University,Stanford, CA USA
bÅstrand Laboratory of Work Physiology, The Swedish School of Sport and Health Sciences, Stockholm, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Daryl Waggott
aDivision of Cardiovascular Medicine, Department of Medicine, Stanford University,Stanford, CA USA
cCenter for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Heidi Salisbury
cCenter for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jeffrey W. Christle
aDivision of Cardiovascular Medicine, Department of Medicine, Stanford University,Stanford, CA USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Trevor Hastie
dDepartment of Statistics, Stanford University, Stanford, CA USA
eDepartment of Biomedical Data Science, Stanford University, Stanford, CA USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Matthew T. Wheeler
aDivision of Cardiovascular Medicine, Department of Medicine, Stanford University,Stanford, CA USA
cCenter for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Euan A. Ashley
aDivision of Cardiovascular Medicine, Department of Medicine, Stanford University,Stanford, CA USA
cCenter for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University Stanford, CA, USA
eDepartment of Biomedical Data Science, Stanford University, Stanford, CA USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Background The ability to measure activity and physiology through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown.

Objective To assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework.

Methods We evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 ± 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination.

Results Devices reported the lowest error for cycling and the highest for walking. Device error was higher for males,greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest.

Conclusions Most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/).

(EE)
Energy expenditure
(HR)
Heart rate
(GEE)
General estimating equation

Footnotes

  • The authors have no competing interests to declare. The authors have no industry relationships to declare.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
Back to top
PreviousNext
Posted December 17, 2016.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort
Anna Shcherbina, C. Mikael Mattsson, Daryl Waggott, Heidi Salisbury, Jeffrey W. Christle, Trevor Hastie, Matthew T. Wheeler, Euan A. Ashley
bioRxiv 094862; doi: https://doi.org/10.1101/094862
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort
Anna Shcherbina, C. Mikael Mattsson, Daryl Waggott, Heidi Salisbury, Jeffrey W. Christle, Trevor Hastie, Matthew T. Wheeler, Euan A. Ashley
bioRxiv 094862; doi: https://doi.org/10.1101/094862

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4228)
  • Biochemistry (9107)
  • Bioengineering (6751)
  • Bioinformatics (23944)
  • Biophysics (12089)
  • Cancer Biology (9495)
  • Cell Biology (13741)
  • Clinical Trials (138)
  • Developmental Biology (7616)
  • Ecology (11661)
  • Epidemiology (2066)
  • Evolutionary Biology (15479)
  • Genetics (10618)
  • Genomics (14296)
  • Immunology (9463)
  • Microbiology (22792)
  • Molecular Biology (9078)
  • Neuroscience (48890)
  • Paleontology (355)
  • Pathology (1479)
  • Pharmacology and Toxicology (2565)
  • Physiology (3823)
  • Plant Biology (8308)
  • Scientific Communication and Education (1467)
  • Synthetic Biology (2290)
  • Systems Biology (6172)
  • Zoology (1297)