Cited by 18Physical Activity and HealthContext-Aware Activity Recognition SystemsMobile Health and mHealth Applications

Validity and Reliability Evaluation of Four Commercial Activity Trackers' Step Counting Performance

Tophøj, Katrine Hauer, Petersen, Matilde Grøndahl, Sæbye, Casper, Baad-Hansen, Thomas, Wagner, Stefan·2018·Telemedicine and e-Health

Abstract

INTRODUCTION: Activity trackers are useful tools for physical rehabilitation purposes. Most available activity trackers are designed for fitness and wellness use, lacking in both accuracy and precision at lower speeds. Validity and reliability at all clinically relevant speeds are crucial selection criteria for use in clinical practice. The aim of this study was to assess the validity and reliability of four consumer-based activity trackers at clinical relevant walking speeds for patient groups undergoing rehabilitation. METHODS: The four commercial activity trackers Fitbit Surge (FS), Fitbit Charge HR (FC), Microsoft Band 2 (MB), and A&D 101NFC Activity Monitor (A&D) were evaluated at 2, 4, 4.5, and 5.5 km/h. Twenty healthy participants aged 25.6 ± 2 years walked on a treadmill at the four velocities in two trials of 100 steps each. Mean average percentage error (MAPE), intraclass correlation coefficient (ICC), and Bland-Altman 95% limits of agreement were calculated to assess validity and reliability. RESULTS: MAPE levels were between -8% and -6% for FS, -15% and 0% for MB, 7% and 21% for FC, and -53% and 1% for AD. The biggest inaccuracies were seen at 2 km/h, where AD underestimated by 53%. The highest accuracy was predominantly found with MB and AD, which overestimated ≤2% at velocities ≥4 km/h. ICC was moderate (0.73) for FS, good (0.88) for MB, moderate (0.52) for FC, and excellent (0.98) for AD. CONCLUSIONS: MB, FS, and AD accurately counted steps, when participants walked with velocities corresponding to a brisk walk (≥4 km/h). Walking at lower speeds (≤2 km/h) was not counted accurately. Thus, the four evaluated activity trackers are not useful for patient groups walking at lower speeds during rehabilitation, nor for counting indoor walking.

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Crossref · 10.1089/tmj.2017.0264

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References 17 · Cited by 18

Authors
Tophøj, K. H., Petersen, M. G., Sæbye, C., Baad-Hansen, T., & Wagner, S.
Affiliations
  • Aarhus University (DK)
  • Aarhus University Hospital (DK)
  • Department of Orthopedic Surgery, Aarhus University Hospital, Aarhus, Denmark.
Corresponding author
Petersen, Matilde Grøndahl
Venue
Telemedicine and e-Health
Published
2018-09
Volume
24
Issue
9
Pages
669-677
ISSN
  • 1530-5627 (ISSN-L)
  • 1556-3669
OpenAlex
W2781981952
Cited by
18
References
17
Citations by year
2026: 1 · 2025: 1 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 6 · 2020: 3 · 2019: 2
FWCI
1.90
Type
journal article
Language
en
Open access
closed
Locations
  • Telemedicine Journal and e-Health (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Physiology › Physical Activity and Health
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Keywords
wearable activity trackers, step counting, wearable devices, walking speed, physical rehabilitation, device accuracy, Fitbit, treadmill walking, indoor walking, consumer health technology
MeSH terms
Walking Speed, Fitness Trackers, Adult, Female, Humans, Male, Reproducibility of Results, Walking, Young Adult, Accelerometry

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