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Cited by 53Physical Activity and HealthOccupational Health and PerformanceContext-Aware Activity Recognition Systems

Wrist-worn accelerometers in assessment of energy expenditure during intensive training

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Kinnunen, H, Tanskanen, M, Kyröläinen, H, Westerterp, K R·2012·Physiological Measurement
DOI 10.1088/0967-3334/33/11/1841
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Abstract

We assessed the ability of the Polar activity recorder (AR) to measure energy expenditure (EE) during military training. Twenty-four voluntary male conscripts participated in the study and wore an AR on the non-dominant wrist 24 h a day for 7 d. The AR analyzed and stored the frequency of hand movements (f_hand) into memory at 1 min intervals. The relationship between f_hand and EE was studied over a 7 d period of military training using the doubly labeled water (DLW) technique. In addition, the relationship between f_hand and EE was analyzed during walking and running on a treadmill with an indirect calorimeter (IC), and f_hand was measured during a supervised 45 min field march test where the conscripts carried combat gear. EE was expressed as physical activity level (PAL), total energy expenditure (TEE), and activity-induced energy expenditure adjusted for body mass (AEE/BM). Over the 7 d period, f_hand alone explained 46% of inter-individual variation in PAL(DLW). After inclusion of body height and mass in the model used to predict PAL(DLW) from f_hand, a very high positive correlation and a low standard error of estimate (SEE) were observed between the AR and DLW techniques: for TEE r = 0.86 (p < 0.001), the SEE was 6.3%, and for AEE/BM r = 0.84 (p < 0.001), the SEE was 12.8%. In the treadmill exercise, f_hand correlated highly with PAL(IC) (r = 0.97 ± 0.02). In the 45 min field march test, the AR measured similar f_hand as on the treadmill at the same speed. In conclusion, the wrist-worn AR can be regarded as a reliable and valid method for assessing EE during intensive training.

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  • The Polar Active has shown to correlate (r2=0.74) with the doubly labeled water technique for assessing energy expenditure during military training.

    “The Polar Active has shown to correlate (r2=0.74) with the doubly labeled water technique for assessing energy expenditure during military training, which related to the study setting [82].”

    From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [82]

    Table 2 reports a correlation of r = 0.86 between wrist-device and doubly labeled water estimates of total energy expenditure during seven days of military training; squaring it gives r² ≈ 0.74. However, section 2.3 identifies the device as a Polar AR prototype of the Polar FA20, not the Polar Active named in the claim. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

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Related

Authors
Kinnunen, H., Tanskanen, M., Kyröläinen, H., & Westerterp, K. R.
Affiliations
  • Polar (Finland) (FI)
  • University of Jyväskylä (FI)
  • Maastricht University (NL)
Corresponding author
Kinnunen, H
ORCID
Venue
Physiological Measurement
Publisher
IOP Publishing
Published
2012-10-31
Volume
33
Issue
11
Pages
1841-1854
ISSN
  • 0967-3334 (ISSN-L)
  • 1361-6579
DOI
10.1088/0967-3334/33/11/1841
OpenAlex
W2011216090
Cited by
53
References
39
Citations by year
2026: 2 · 2025: 1 · 2024: 3 · 2023: 2 · 2022: 6 · 2021: 4 · 2020: 6 · 2019: 11 · 2018: 2 · 2017: 5 · 2016: 2 · 2015: 2 · 2014: 2 · 2013: 5
FWCI
1.93
Type
journal article
Language
en
Open access
Locations
  • Physiological Measurement (publishedVersion)
  • PubMed (publishedVersion)
  • Research Publications (Maastricht University) (publishedVersion, other-oa)
  • Research Publications (Maastricht University) (submittedVersion, other-oa)
Funders
Suomen Kulttuurirahasto
Topics
  • Health Sciences › Medicine › Physiology › Physical Activity and Health
  • Health Sciences › Health Professions › Occupational Therapy › Occupational Health and Performance
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
Keywords
wrist-worn accelerometers, energy expenditure, military education, physical activity level, doubly labeled water, treadmill walking and running
MeSH terms
Energy Metabolism, Exercise Test, Humans, Male, Military Personnel, Running, Wrist, Reproducibility of Results, Exercise, Linear Models, Walking, Young Adult, Accelerometry

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