Cited by 69Physical Activity and HealthCardiovascular and exercise physiologyContext-Aware Activity Recognition Systems

Estimating relative intensity using individualized accelerometer cutpoints: the importance of fitness level

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Ozemek, Cemal, Cochran, Heather L, Strath, Scott J, Byun, Wonwoo, Kaminsky, Leonard A·2013·BMC Medical Research Methodology

Abstract

BACKGROUND: Accelerometer cutpoints based on absolute intensity may under or overestimate levels of physical activity due to the lack of consideration for an individual's current fitness level. The purpose of this study was to illustrate the interindividual variability in accelerometer activity counts measured at relative intensities (40 and 60% heart rate reserve (HRR)) and demonstrate the differences between relative activity counts between low, moderate and high fitness groups. METHODS: Seventy-three subjects (38 men, 35 women) with a wide range of cardiorespiratory fitness (maximal oxygen consumption (VO2max): 27.9 to 58.5 ml · kg⁻¹ · min⁻¹), performed a submaximal exercise test with measures of heart rate (HR) and accelerometer activity counts. Linear regression equations were developed for each subject to determine accelerometer activity counts for moderate and vigorous intensity physical activity corresponding to 40% and 60% of HRR. Interindividual variability of activity counts between subjects at both 40% and 60% of HRR was demonstrated by plotting values using a box and whisker plot. To examine the difference between absolute and relative activity cutpoints, subjects were categorized into 3 fitness groups based on metabolic equivalents (MET) (<10 MET, 10-13 MET, >13 MET). RESULTS: At 40 and 60% of HRR, activity counts ranged from 1455-7520, and 3459-10066 counts · min-1, respectively. Activity counts at 40% HRR (3385 ± 850, 4048 ± 1090, and 5037 ± 1019 counts · min⁻¹) and 60% HRR (5159 ± 765, 5995 ± 1131 and 7367 ± 1374 counts · min-1) significantly increased across fitness groups (<10 MET, 10-13 MET, and >13 MET, respectively). CONCLUSION: This study revealed interindividual variability in activity counts at relative moderate (40% HRR) and vigorous (60% HRR) intensities, while fitness level was shown to have a significant influence on relative activity counts measured at these intensities. Individualizing activity count cutpoints may be more representative of an individual's PA level relative to their fitness capacity, compared to absolute activity count cutpoints.

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  • Accelerometers are not suitable for measuring activities such as cycling and swimming, and the accelerometer thresholds for moderate and vigorous intensity activity levels are problematic in older adults.

    “Furthermore, accelerometers are not suitable for measuring activities such as cycling and swimming, and the accelerometer thresholds for moderate and vigorous intensity activity levels are problematic in older adults.21 22”

    From Effect of exercise training for five years on all cause mortality in older adults—the Generation 100 study: randomised controlled trial (2020) · cites this paper as [21]

    The Background (page unavailable) says standard moderate- and vigorous-intensity accelerometer cutpoints can underestimate activity intensity in adults over 60. Our copy does not address whether accelerometers are unsuitable for measuring cycling or swimming; searches for those activities and non-ambulatory limitations found no supporting passage. (LLM, conf=0.86)

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  1. American College of Sports Medicine Thompson WG, Gordon NF, Pescatello LS American College of Sports Medicine Guidelines for Exercise Testing and Prescription 2010 8 Philadelphia, PA: Wolters Kluwer/Lippincott Williams & Wilkins

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Authors
Ozemek, C., Cochran, H. L., Strath, S. J., Byun, W., & Kaminsky, L. A.
Affiliations
  • Ball State University (US)
  • Indiana University Health (US)
  • University of Wisconsin–Milwaukee (US)
Corresponding author
Ozemek, Cemal
Venue
BMC Medical Research Methodology
Published
2013-04-01
Volume
13
Issue
1
Pages
53-53
ISSN
1471-2288 (ISSN-L)
OpenAlex
W2092575482
Cited by
69
References
38
Citations by year
2026: 1 · 2025: 2 · 2023: 3 · 2022: 7 · 2021: 6 · 2020: 11 · 2019: 9 · 2018: 8 · 2017: 5 · 2016: 7 · 2015: 7 · 2014: 2 · 2013: 1
FWCI
3.95
Type
journal article
Language
en
Open access
Locations
  • BMC Medical Research Methodology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • National Institutes of Health (UL1TR000055)
  • National Center for Advancing Translational Sciences
Topics
  • Health Sciences › Medicine › Physiology › Physical Activity and Health
  • Health Sciences › Medicine › Complementary and alternative medicine › Cardiovascular and exercise physiology
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
Keywords
relative intensity, heart rate reserve, cardiorespiratory fitness, VO2max, metabolic equivalents, moderate-to-vigorous physical activity, interindividual variability, submaximal exercise testing, physical activity monitoring, linear regression equations, exercise intensity estimation, sedentary behavior
MeSH terms
Adult, Aged, Exercise Test, Physical Exertion, Female, Heart Rate, Humans, Male, Middle Aged, Motor Activity, Oxygen Consumption, Physical Fitness, Exercise, Accelerometry

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