Cited by 2,033Physical Activity and HealthContext-Aware Activity Recognition SystemsObesity, Physical Activity, Diet

Conducting accelerometer-based activity assessments in field-based research

TROST, STEWART G., MCIVER, KERRY L., PATE, RUSSELL R.·2005·Medicine & Science in Sports & Exercise

Abstract

PURPOSE: The purpose of this review is to address important methodological issues related to conducting accelerometer-based assessments of physical activity in free-living individuals. METHODS: We review the extant scientific literature for empirical information related to the following issues: product selection, number of accelerometers needed, placement of accelerometers, epoch length, and days of monitoring required to estimate habitual physical activity. We also discuss the various options related to distributing and collecting monitors and strategies to enhance compliance with the monitoring protocol. RESULTS: No definitive evidence exists currently to indicate that one make and model of accelerometer is more valid and reliable than another. Selection of accelerometer therefore remains primarily an issue of practicality, technical support, and comparability with other studies. Studies employing multiple accelerometers to estimate energy expenditure report only marginal improvements in explanatory power. Accelerometers are best placed on hip or the lower back. Although the issue of epoch length has not been studied in adults, the use of count cut points based on 1-min time intervals maybe inappropriate in children and may result in underestimation of physical activity. Among adults, 3-5 d of monitoring is required to reliably estimate habitual physical activity. Among children and adolescents, the number of monitoring days required ranges from 4 to 9 d, making it difficult to draw a definitive conclusion for this population. Face-to-face distribution and collection of accelerometers is probably the best option in field-based research, but delivery and return by express carrier or registered mail is a viable option. CONCLUSION: Accelerometer-based activity assessments requires careful planning and the use of appropriate strategies to increase compliance.

Integrity signals

Registry

Crossref · 10.1249/01.mss.0000185657.86065.98

Cites

42 of 42 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
TROST, S. G., MCIVER, K. L., & PATE, R. R.
Affiliations
  • Kansas State University (US)
  • University of South Carolina (US)
Venue
Medicine & Science in Sports & Exercise
Published
2005-11
Volume
37
Issue
11
Pages
S531-S543
ISSN
0195-9131 (ISSN-L)
OpenAlex
W1527268501
Cited by
2,033
References
42
Citations by year
2026: 51 · 2025: 85 · 2024: 122 · 2023: 132 · 2022: 96 · 2021: 100 · 2020: 141 · 2019: 108 · 2018: 109 · 2017: 131 · 2016: 124 · 2015: 118 · 2014: 128 · 2013: 150 · 2012: 107
FWCI
19.38
Type
journal article
Language
en
Open access
closed
Locations
  • Medicine & Science in Sports & Exercise (publishedVersion)
  • PubMed (publishedVersion)
  • Scholar Commons (University of South Carolina) (submittedVersion)
  • Faculty of Health
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 › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
Keywords
accelerometer, physical activity measurement, free-living physical activity, accelerometer placement, epoch length, monitoring duration, children and adolescents, physical activity behavior, energy expenditure
MeSH terms
Acceleration, Electronic Data Processing, Humans, Locomotion, Research Design, United States, Reproducibility of Results, Ergometry, Guidelines as Topic, Evidence-Based Medicine

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review