The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
Assessing Physical Activity Using Wearable Monitors: Measures of Physical Activity
Open accessAbstract
BACKGROUND: Physical activity may be defined broadly as "all bodily actions produced by the contraction of skeletal muscle that increase energy expenditure above basal level." Physical activity is a complex construct that can be classified into major categories qualitatively, quantitatively, or contextually. The quantitative assessment of physical activity using wearable monitors is grounded in the measurement of energy expenditure. Six main categories of wearable monitors are currently available to investigators: pedometers, load transducers/foot-contact monitors, accelerometers, HR monitors, combined accelerometer and HR monitors, and multiple sensor systems. BEST PRACTICES: Currently available monitors are capable of measuring total physical activity as well as components of physical activity that play important roles in human health. The selection of wearable monitors for measuring physical activity will depend on the physical activity component of interest, study objectives, characteristics of the target population, and study feasibility in terms of cost and logistics. FUTURE DIRECTIONS: Future development of sensors and analytical techniques for assessing physical activity should focus on the dynamic ranges of sensors, comparability for sensor output across manufacturers, and the application of advanced modeling techniques to predict energy expenditure and classify physical activities. New approaches for qualitatively classifying physical activity should be validated using direct observation or recording. New sensors and methods for quantitatively assessing physical activity should be validated in laboratory and free-living populations using criterion methods of calorimetry or doubly labeled water.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The text we found for this paper looks like another document, so the self-check wasn’t run.
Citations
Cites
Compendium of Physical Activities: Classification of energy costs of human physical activities
AINSWORTH, B. E., HASKELL, W. L., LEON, A. S., JACOBS, D. R., MONTOYE, H. J., SALLIS, J. F., & PAFFENBARGER, R. S. (1993) · Medicine & Science in Sports & Exercise · doi:10.1249/00005768-199301000-00011 · Cited by 4,102
Scaling Why is animal size so important?
Schmidt‐Nielsen, K. (1984) · Cited by 2,654
Kleiber, M. (1947) · Physiological Reviews · doi:10.1152/physrev.1947.27.4.511 · Cited by 1,817
Validation and Calibration of Physical Activity Monitors in Children
Puyau, M. R., Adolph, A. L., Vohra, F. A., & Butte, N. F. (2002) · Obesity Research · doi:10.1038/oby.2002.24 · Cited by 1,013
Self-citationThe Technology of Accelerometry-Based Activity Monitors: Current and Future
CHEN, K. Y., & BASSETT, D. R. (2005) · Medicine & Science in Sports & Exercise · doi:10.1249/01.mss.0000185571.49104.82 · Cited by 996
Accelerometry: A technique for quantifying movement patterns during walking
Kavanagh, J. J., & Menz, H. B. (2008) · Gait & Posture · doi:10.1016/j.gaitpost.2007.10.010 · Cited by 661
Physical Activity Assessment With Accelerometers: An Evaluation Against Doubly Labeled Water
Plasqui, G., & Westerterp, K. R. (2007) · Obesity · doi:10.1038/oby.2007.281 · Cited by 654
Self-citationAccuracy and Reliability of 10 Pedometers for Measuring Steps over a 400-m Walk
SCHNEIDER, P. L., Crouter, S. E., Lukajic, O., & Bassett, D. R. (2003) · Medicine & Science in Sports & Exercise · doi:10.1249/01.mss.0000089342.96098.c4 · Cited by 633
Development of a Compendium of Energy Expenditures for Youth.
Ridley, K., Ainsworth, B. E., & Olds, T. (2008) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/1479-5868-5-45 · Cited by 622
How to assess physical activity? How to assess physical fitness?
Vanhees, L., Lefevre, J., Philippaerts, R. M., Martens, M., Huygens, W., Troosters, T., & Beunen, G. P. (2005) · European Journal of Cardiovascular Prevention & Rehabilitation · doi:10.1097/01.hjr.0000161551.73095.9c · Cited by 595
Flagged first, then by citations
Cited by
Sorted by citations
Items 301–357 of 357
Abidin, N. Z., Muhamed, A. M. C., & Singh, R. (2016) · Movement Health & Exercise · doi:10.15282/mohe.v5i1.102
“…PA levels of older Malay adults assessed by tri-axial accelerometer and categorizing the PA intensity using cut-points for VM. Compared to previous models, the addition of the third axis, the mediolateral (ML) axis, provides a more comprehensive assessment of body movements (Butte et al., 2012).”
BackgroundMethodInfluentialOptical fiber head for monitoring of heart rate and blood oxygenation
Hoffmann, K., Baranowska, A., Żmojda, J. M., Kochanowicz, M., & Dorosz, D. (2016) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2249165
“We are capable of constructing surgeon robots [1, 2], life supporting devices [3] and human health monitor [4, 5].”
BackgroundGait monitoring : from the clinics to the daily life
Storm, F. A. (2016) · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York)
Maternal physical activity: influence on maternal and delivery outcomes
Watson, E. D. (2016)
Estimation of VO2max from walk exercises with heart rate and accelerometer
정은지, 김경애, Hong, G., Sun, L. B., Choi, H., 박준성, Nho, H., & Doh, H. (2017) · Korean Journal of Sport Science · doi:10.24985/kjss.2017.28.1.37
Objectively measured sedentary behaviour, physical activity and health in adolescent females
Dowd, K. (2012) · University of Limerick Institutional Repository (University of Limerick) · doi:10.34961/7228
Energy Requirements and Body Composition of Professional Team-Sport Athletes
Walker, E. (2016) · Victoria University Research Repository (Victoria University)
Monitoring System for Elderly Care with Smartwatch and Smartphone
Rosales, P., Vega, A. L., Marziani, C. D., Gallardo, J. I., Pires, J. L. D. S., & Alcoleas, R. (2017) · El Servicio de Difusión de la Creación Intelectual (National University of La Plata)
Effects of exercise on hunger, food intake and energy expenditure
Rocha, J. (2013) · SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University)
Novel insights into the physical activity continuum and cardiometabolic health in adults
Powell, C. (2017) · University of Limerick Institutional Repository (University of Limerick) · doi:10.34961/7196
손윤선, Kwang, K. J., Lee, D., 황봉연, 이종도, & 김기언 (2016) · The Korean Journal of Measurement and Evaluation in Physical Education and Sports Science · doi:10.21797/ksme.2016.18.2.001
Validation of K-Sense against indirect calorimetry and accelerometry
Yli-Piipari, S. R., Zaman, K. I., Fish, J. C., & Hnat, T. W. (2019) · Human Movement · doi:10.5114/hm.2019.79042
“Accelerometers are typically designed to categorize the duration and intensity of habitual PA of humans [15].”
BackgroundWearable Computing and Human-Centricity
Tadayon, A., Tadayon, R., McDaniel, T. L., & Panchanathan, S. (2019) · Studies in systems, decision and control · doi:10.1007/978-3-319-92384-0_12
Interventions for increased physical activity among office workers
Wahlström, V. (2019) · DiVA at Umeå University (Umeå University)
Gwam, C. U., Mohamed, N. S., Castrodad, I. M. D., Wilkie, W. A., Remily, E. A., Mahajan, A. K., Patel, N. G., Andrews, T.-J., Gesheff, M. G., & Delanois, R. E. (2019) · Hong Kong Journal of Orthopaedic Research · doi:10.37515/ortho.8231.2304
Nehrkorn-Bailey, A. M. (2019) · The Research Repository @ WVU (West Virginia University) · doi:10.33915/etd.3896
“Assessing heart rate is a validated method to measure physical activity intensity, as heart rate is associated with energy expenditure (Butte et al., 2012; Watkinson et al., 2010).”
MethodWalkability Around the Worksite and Physical Activity
Hurley, J. C. (2019)
White, B. (2020) · Otago University Research Archive (University of Otago)
Dairo, Y. M. (2017) · Radar (Oxford Brookes University) · doi:10.24384/a8tb-w925
Knoxville Moves: Log-in and Get Mobile
Monroe, C. M. (2014)
Automatic Detection of Situational Context Using AI from Minimal Sensor Modality
Mitra, N., & Morshed, B. I. (2022) · IEEE International Conference on Electro Information Technology · doi:10.1109/eit53891.2022.9813854
Quality of Experience and Mental Energy Use of Cobot Workers in Manufacturing Enterprises
Storm, F. A., Negri, L., Carissoli, C., Fernández, A. P., Dei, C., Bassi, M., Berckmans, D., & Fave, A. D. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-35741-1_33
Low-Mobility Complementary Tool for Patient Follow-Up: A Proof of Concept for E-Health
Muhoza, A. C., Bergeret, E., Brdys, C., & Gary, F. (2023) · IEEE Symposium on Computers and Communications (ISCC) · doi:10.1109/iscc58397.2023.10218122
“, physical activity refers to all bodily movements that increase energy expenditure above basal levels [1].”
BackgroundBogachev, M. I., Grigarevichius, K. R., Сергеевич, П. Н., Анатольевна, П. С., Tsygankova, M., Plotnikova, E., Ageeva, T. V., & Mukhamedshina, Y. O. (2024) · Journal of the Russian Universities Radioelectronics · doi:10.32603/1993-8985-2024-27-3-108-123
Lange‐Maia, B. S., Wang, T., Oveisgharan, S., Hausdorff, J. M., Bennett, D. A., & Buchman, A. S. (2024) · The Journals of Gerontology Series A · doi:10.1093/gerona/glae238 · Cited by 1
Karapetyan, S., Zeileis, A., Henriksen, A., & Hapfelmeier, A. (2024) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.1093/jrsssc/qlae077 · Cited by 1
“There is currently a wide range of accelerometers available, for use in both research (Henriksen, Haugen Mikalsen, et al., 2018) and the consumer market (Butte et al., 2012).”
Sirard, J. R., Kumar, T., Marcotte, R. T., Chase, J. D., Cox, M. F., Amalbert‐Birriel, M. A., & STAUDENMAYER, J. W. (2025) · Journal for the Measurement of Physical Behaviour · doi:10.1123/jmpb.2024-0031
Banerjee, S., & Pal, S. R. (2024) · FoodSci Indian Journal of Research in Food Science and Nutrition · doi:10.15613/fijrfn/2023/v10i2/223412
Gong, F., & Yang, F. (2025) · Research Square · doi:10.21203/rs.3.rs-6309936/v1
Luzar, M., Ostrowski, K., Kasperowicz, R., Semegen, M., & Korbicz, J. (2025) · International Conference on Methods and Models in Automation and Robotics · doi:10.1109/mmar65820.2025.11150915
Wang, Z., Zou, P., Liu, M., Ruan, L., Niu, B., Zhang, C., Chen, L., & Zhang, Y. (2025) · International Journal of Surgery · doi:10.1097/js9.0000000000004444
Davies, B. R. (2013) · University of Bedfordshire Repository (University of Bedfordshire)
Pulsford, R. M., Brocklebank, L. A., Fenton, S. A. M., Bakker, E., Mielke, G. I., Tsai, L.-T., Atkin, A. J., Harvey, D. L., Blodgett, J. M., Ahmadi, M., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22622464
de Wolf, I., Elevelt, A., van Nassau, F., Toepoel, V., de Hollander, E., Kompier, M. E., Luiten, A., Schouten, B., Wendel-Vos, G., & Ploeg, H. P. V. D. (2024) · Figshare · doi:10.6084/m9.figshare.26170597
Pulsford, R. M., Brocklebank, L. A., Fenton, S. A. M., Bakker, E., Mielke, G. I., Tsai, L.-T., Atkin, A. J., Harvey, D. L., Blodgett, J. M., Ahmadi, M., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22622467
Pulsford, R. M., Brocklebank, L. A., Fenton, S. A. M., Bakker, E., Mielke, G. I., Tsai, L.-T., Atkin, A. J., Harvey, D. L., Blodgett, J. M., Ahmadi, M., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22622458
de Wolf, I., Elevelt, A., van Nassau, F., Toepoel, V., de Hollander, E., Kompier, M. E., Luiten, A., Schouten, B., Wendel-Vos, G., & Ploeg, H. P. V. D. (2024) · Figshare · doi:10.6084/m9.figshare.26170668
de Müllenheim, P. (2016) · theses.fr (ABES) · doi:10.70675/6d31aae1z0118z4f71zb382z54db5db6f6ab
Multi-Sensor Based Activity Recognition˸ Development and Validation in Real-Life context
Rahman, H. A. (2017) · theses.fr (ABES) · doi:10.70675/8c855d1fz7000z4815zab29z33f2730fb1ee
Wooten, S. V., Cantoni, B., Audirac, M., Gilchrist, S. C., Livingston, J. A., Roth, M. E., Zigler, C. M., & Kleinerman, E. S. (2026) · JMIR Cancer · doi:10.2196/87591
“In addition to wearable devices being capable of providing long-term activity data [6-8], it has been well established that PA monitoring can inform exercise prescription decisions and quantify exercise intervention participation [9-11].”
Bioelectrocatalytic Evaluation of Redox Dynamics in Exercise Physiology
Ma, G., Wei, X., & Gang, T. (2026) · Electroanalysis · doi:10.1002/elan.70139
Kitano, N., Kawakami, R., Fujii, Y., Yamaguchi, D., Muramatsu, Y., Matsushita, Y., Mizuno, Y., Miyamoto, S., Yoshida, T., Kai, Y., et al. (2026) · PLoS ONE · doi:10.1371/journal.pone.0350144
Villarreal‒Jaimes, C. A., Julián David Rojas, D., Candela-Becerra, L. J., Jose Pedro Mora, O., & Carlos Alberto Ríos, R. (2026) · Proceedings of the Geologists Association · doi:10.1016/j.pgeola.2026.101198
Guo, M., Wang, R., Vos, S. B., Houben, S., & Hu, J. (2026) · Entertainment Computing · doi:10.1016/j.entcom.2026.101197
Zhang, Y., Zhang, Y., Zhang, X., Luo, H., & Kong, H. (2026) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2026.103778
Hu, W., Zhang, H., Liang, B., Wu, M., & Kortas, J. A. (2026) · Applied Sciences · doi:10.3390/app16178490
“Research during this period primarily emphasized activity classification, physical activity assessment, and energy expenditure estimation using accelerometer and inertial sensor data [42,43].”
Arslan, S. A., Gürbüz, A. K., Yılmaz, B. Ş., & Keskin, D. (2026) · SN Comprehensive Clinical Medicine · doi:10.1007/s42399-026-02659-3
“Physical activity (PA) is body movement produced by skeletal muscles that increases energy expenditure [1, 2].”
de Wolf, I., Snoeker, B. A. M., Dekkers, C., Hanning-Vooijs, C., Kompier, M. E., van Nassau, F., Wendel‐Vos, W., van der Ploeg, H. P., & Toepoel, V. (2026) · Journal of Physical Activity and Health · doi:10.1123/jpah.2026-0289
McGinley, S. K. (2014) · Libraries and Cultural Resources (University of Calgary) · doi:10.11575/prism/25991
Metadata
- Authors
- BUTTE, N. F., EKELUND, U., & WESTERTERP, K. R.
- Affiliations
- Agricultural Research Service (US)
- University of Cambridge (GB)
- Maastricht University (NL)
- Venue
- Medicine & Science in Sports & Exercise
- Published
- 2012-01
- Volume
- 44
- Issue
- 1S
- Pages
- S5-S12
- ISSN
- 0195-9131 (ISSN-L)
- OpenAlex
- W2329242152
- Cited by
- 359
- References
- 51
- Citations by year
- 2026: 10 · 2025: 18 · 2024: 14 · 2023: 14 · 2022: 14 · 2021: 16 · 2020: 29 · 2019: 23 · 2018: 26 · 2017: 39 · 2016: 38 · 2015: 32 · 2014: 39 · 2013: 29 · 2012: 16
- FWCI
- 2.88
- Type
- journal article
- Language
- en
- Open access
- Licence
- other-oa
- Locations
- Medicine & Science in Sports & Exercise (publishedVersion)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, other-oa)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › 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
- physical activity measurement, wearable monitors, accelerometer, pedometers, heart rate monitors, energy expenditure, physical activity classification, sensor validation, doubly labeled water, calorimetry
- MeSH terms
- Energy Metabolism, Humans, Motor Activity, Exercise, Monitoring, Ambulatory
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