Cited by 359Physical Activity and HealthContext-Aware Activity Recognition SystemsMobile Health and mHealth Applications

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Assessing Physical Activity Using Wearable Monitors: Measures of Physical Activity

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BUTTE, NANCY F., EKELUND, ULF, WESTERTERP, KLAAS R.·2012·Medicine & Science in Sports & Exercise

DOI 10.1249/mss.0b013e3182399c0e

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Abstract

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.

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Compendium of Physical Activities: Classification of energy costs of human physical activities
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BackgroundSelf-citation
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Method
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Background
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Background
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Background
Physical Activity
Moghaddam, G. K., & Lowe, C. R. (2018) · SpringerBriefs in applied sciences and technology · doi:10.1007/978-3-030-01557-2_2 · Cited by 21
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“indirect calorimetry or doubly labelled water) [10], and as objective methods they do not share the bias attributed to subjective methods [7].”
BackgroundMethod
Independent prescribing by advanced physiotherapists for patients with low back pain in primary care: A feasibility trial with an embedded qualitative component
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“PA is a complex construct that relates to the subject’s behavior and that is defined by several domains and dimensions, as well as contextual aspects (dimensions of time and place, position or posture; Butte et al., 2012).”
Background
Validating measures of free-living physical activity in overweight and obese subjects using an accelerometer
Valenti, G., Camps, S. G., Verhoef, S. P. M., Bonomi, A. G., & Westerterp, K. R. (2013) · International Journal of Obesity · doi:10.1038/ijo.2013.195 · Cited by 17
Self-citation
Insights on physical behavior while working from home: An ecological momentary assessment study
Sers, S., Timm, I., de Vries, E. A., Wäsche, H., Wöll, A., Bender, O., & Giurgiu, M. (2023) · Scandinavian Journal of Medicine and Science in Sports · doi:10.1111/sms.14447 · Cited by 20
“Based on the parameters “body position” and “energy expenditure” (MET), as well as in line with the international definition of SB 9 and published thresholds to further specify PA into LPA and MVPA, 30 we classified each minute of the data file as either sleep, LPA, MVPA or SB.”
Method
Assessing physical activity intensity by video analysis
Silva, P., Santiago, C. B., Reis, L. P., Sousa, A. J., Mota, J. A. P. S., & Welk, G. J. (2015) · Physiological Measurement · doi:10.1088/0967-3334/36/5/1037 · Cited by 17
“New approaches for qualitatively classifying PA should be validated using DO or recording (Butte et al 2012).”
Background
The use of individual cut points from treadmill walking to assess free-living moderate to vigorous physical activity in obese subjects by accelerometry: is it useful?
Aadland, E., & Steene‐Johannessen, J. (2012) · BMC Medical Research Methodology · doi:10.1186/1471-2288-12-172 · Cited by 18
“9 and ≥6 metabolic equivalents (METs), respectively [2-4].”
Background
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“Accelerometers measure movement of direction in uniaxial and triaxial planes to indicate frequency, duration, and intensity of activity (17,22).”
Background
Atividade física de mulheres no climatério: comparação entre auto-relato e pedômetro
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Treadmill Calibration of the Actigraph GT1M in Young-to-Middle-Aged Obese-to-Severely Obese Subjects
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“Although definitions and concepts regarding PA intensity are frequently discussed [12, 21–23], the normalization of energy expenditure to body weight is probably critical to arrive at sound PA intensity thresholds and PA recommendations for the obese [18, 24].”
Background
The accuracy of the SenseWear Pro3 and the activPAL3 Micro devices for measurement of energy expenditure
Powell, C., Carson, B. P., Dowd, K., & Donnelly, A. (2016) · Physiological Measurement · doi:10.1088/0967-3334/37/10/1715 · Cited by 16
Dynamic sitting: Measurement and associations with metabolic health
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“Next to the vertical direction, these include the anteroposterior (back-to-front) and mediolateral (side-to-side) directions (Butte et al., 2012).”
Background
Changes in physical activities patterns assessed by accelerometry after bariatric surgery: A systematic review and meta-analysis
Barbosa, C. G. R., Verlengia, R., Ribeiro, A. G. S. V., de Oliveira, M. R. M., & Crisp, A. H. (2018) · Obesity Medicine · doi:10.1016/j.obmed.2018.12.003 · Cited by 15
Development of a measurement setup to detect the level of physical activity and social distancing of ageing people in a social garden during COVID-19 pandemic
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“Furthermore, being inexpensive, portable and lightweight, they are well accepted by users [12].”
Background
Dynamic changes in energy expenditure in response to underfeeding: a review
Egan, A. M., & Collins, A. L. (2021) · Proceedings of The Nutrition Society · doi:10.1017/s0029665121003669 · Cited by 16
Separation of rotational and translational segmental momentum to assess movement coordination during walking
Gaffney, B. M. M., Christiansen, C. L., Murray, A. M., Silverman, A. K., & Davidson, B. S. (2016) · Human Movement Science · doi:10.1016/j.humov.2016.12.001 · Cited by 15
“As wearable sensors become more widely used in a clinical setting (typically for activity monitoring) (Butte et al., 2012; Redfield et al., 2013; Fulk et al., 2014), we anticipate more explorations will focus on how the implementation of wearable sensors can be used to measure or infer biomechanically useful informati…”
Background
Measuring the validity and reliability of the Apple Watch as a physical activity monitor
Zhang, P., Godin, S., & Owens, M. V. (2019) · The Journal of Sports Medicine and Physical Fitness · doi:10.23736/s0022-4707.18.08339-1 · Cited by 15
Kernel Density Estimation as a Measure of Environmental Exposure Related to Insulin Resistance in Breast Cancer Survivors
Jankowska, M. M., Natarajan, L., Godbole, S. V., Meseck, K., Sears, D. D., Patterson, R. E., & Kerr, J. (2017) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-16-0927 · Cited by 15
“The ActiGraph yields valid estimates of physical activity in controlled and free-living environments, and has been validated in older adult populations (43, 44).”
Background
Association between physical activity measured by accelerometry and cognitive function in older adults: a systematic review
de Oliveira, J. J., Ribeiro, A. G. S. V., Silva, J. A. D. O., Barbosa, C. G. R., Silva, A. D. S. E., dos Santos, G. M., Verlengia, R., & Pertille, A. (2023) · Aging & Mental Health · doi:10.1080/13607863.2023.2248477 · Cited by 15
“anteroposterior, and mediolateral), provide data related to physical activity, frequency, duration, and intensity of daily physical activities with greater reliability and accuracy (Butte et al. 2012).”
A study protocol for MindMoves: A lifestyle physical activity and cognitive training intervention to prevent cognitive impairment in older women with cardiovascular disease
Halloway, S., Schoeny, M. E., Barnes, L. L., Arvanitakis, Z., Pressler, S. J., Braun, L. T., Volgman, A. S., Gamboa, C. J., & Wilbur, J. (2020) · Contemporary Clinical Trials · doi:10.1016/j.cct.2020.106254 · Cited by 15
“The ActiGraph GT3XEPlus Triaxial Accelerometer will provide a device measure of physical activity, including minutes per day of light and moderate-vigorous physical activity, corrected for total daily wear time [102,103].”
Method
Niveles de actividad física y acelerometría: recomendaciones y patrones de movimiento en escolares
Cañada, F. C., Torres‐Luque, G., Fernández, I. L., & Carnero, E. Á. (2014) · Cuadernos de Psicología del Deporte · doi:10.4321/s1578-84232014000300014 · Cited by 17
“Medicine and science in sports and exercise, 42(9), 17761784.”
BackgroundInfluential
Individual classification of elementary school children’s physical activity: A time-efficient, group-based approach to reference measurements
Kühnhausen, J., Dirk, J., & Schmiedek, F. (2016) · Behavior Research Methods · doi:10.3758/s13428-016-0724-2 · Cited by 15
“These cut points are based on the recommendations from calibration studies, specifically for children (Butte et al., 2012; Evenson et al., 2008; Freedson et al., 2005; Mattocks et al., 2007; Pulsford et al., 2011; Puyau et al., 2002).”
Method
Single parent status and children’s objectively measured level of physical activity
Singhammer, J., Ried‐Larsen, M., Møller, N. C., Lund-Kristensen, P., Froberg, K., & Andersen, L. B. (2015) · Sports Medicine - Open · doi:10.1186/s40798-015-0020-1 · Cited by 14
“Children’s level of physical activity (PA) declines from adolescence [1] and remains low throughout adulthood for many individuals [2], thereby increasing the risk for later cardio-metabolic diseases (CMD) [3].”
Background
The Aging trial: Design of a randomized controlled trial to increase physical activity in middle-aged and older adults
Diehl, M. K., Nehrkorn-Bailey, A. M., Thompson, K., Rodriguez, D., Li, K., Rebok, G. W., Roth, D. L., Chung, S.-E., Bland, C., Feltner, S., et al. (2020) · Contemporary Clinical Trials · doi:10.1016/j.cct.2020.106105 · Cited by 16
“walking), as well as the intensity, duration, and frequency of activity throughout the day (14,101).”
Deep Learning to Predict Energy Expenditure and Activity Intensity in Free Living Conditions using Wrist-specific Accelerometry
Nawaratne, R., Alahakoon, D., Silva, D. D., O’Halloran, P., Montoye, A. H. K., Staley, K., Nicholson, M., & Kingsley, M. (2020) · Journal of Sports Sciences · doi:10.1080/02640414.2020.1841394 · Cited by 13
“(Butte et al., 2012; Kanagasabai & Chaput, 2017).”
Personalized cardiorespiratory fitness and energy expenditure estimation using hierarchical Bayesian models
Altini, M., Casale, P., Penders, J., & Amft, O. (2015) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2015.06.008 · Cited by 13
“Low-power wearable sensing for mHealth promises to raise the quality of health monitoring in every-day life environments [13].”
Background
A wireless accelerometer node for reliable and valid measurement of lumbar accelerations during treadmill running
Lindsay, T. R., Yaggie, J. A., & McGregor, S. J. (2016) · Sports Biomechanics · doi:10.1080/14763141.2015.1123760 · Cited by 13
The importance of physical activity and health for physical therapy
Hagströmer, M., & Franzén, E. (2017) · Physical Therapy Reviews · doi:10.1080/10833196.2017.1314687 · Cited by 13
Objectively measured the impact of ambient air pollution on physical activity for older adults
Cheng, J., Wu, Y., Wang, X., & Yu, H. (2024) · BMC Public Health · doi:10.1186/s12889-024-18279-2 · Cited by 13
“Physical Activity data were measured using an accelerometer (ActiGraph GT3X-BT), which is a reliable and valid objective measure [43].”
Method
Occupational physical activity assessment for chronic disease prevention and management: A review of methods for both occupational health practitioners and researchers
Scott, K. A., & Browning, R. C. (2016) · Journal of Occupational and Environmental Hygiene · doi:10.1080/15459624.2016.1143946 · Cited by 14
Are Esports Players Inactive? A Systematic Review
Voisin, N., Besombes, N., & Laffage-Cosnier, S. (2022) · Physical Culture and Sport Studies and Research · doi:10.2478/pcssr-2022-0022 · Cited by 12
Matching physical work demands with functional capacity in healthy workers: Can it be more efficient?
Soer, R., Hollak, N., Deijs, M., van der Woude, L. H. V., & Reneman, M. F. (2014) · Applied Ergonomics · doi:10.1016/j.apergo.2014.01.011 · Cited by 12
“A combination of accelerometers and HR monitors is assumed to be more accurate and precise (Butte et al., 2012) and is recommended in future studies.”
Background
Sensor-embedded and electronics textiles: A review on advanced materials, manufacturing, and applications
Abtew, M. A., Ahmmed, A. S., Tadesse, M. G., & Zaman, S. U. (2025) · Textile Research Journal · doi:10.1177/00405175251338152 · Cited by 12
Unobtrusive health monitoring system using video-based physiological information and activity measurements
Fernández, A., Candás, J. L. C., Usamentiaga, R., Álvarez-Álvarez, E., & Casado, R. (2015) · International Conference on Computer, Information and Telecommunication Systems · doi:10.1109/cits.2015.7297728 · Cited by 11
“They are small, lightweight and portable, and motion can be recorded to provide an indication of the frequency, duration, and intensity of activities [11].”
Background
Estimation of physical activity monitored during the day-to-day life by an autonomous wearable device (SVELTE project)
Doron, M., Bastian, T., Maire, A., Dugas, J., Perrin, E., Gris, F., Guillemaud, R., Deschamps, T., Bianchi, P., Caritu, Y., et al. (2013) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2013.6610579 · Cited by 11
A novel pervasive computing method to enhance efficiency of walking activity
Bodaghi, A. (2016) · Health and Technology · doi:10.1007/s12553-016-0138-2 · Cited by 11
“Moreover, in some cases, they might provide a record of past activities [5, 10, 20 – 22].”
Background
The role of a behavioural medicine intervention in physiotherapy for the effects of rehabilitation outcomes in exercise-based cardiac rehabilitation (ECRA) – the study protocol of a randomised, controlled trial
Borg, S., Öberg, B. E., Nilsson, L., Söderlund, A., & Bäck, M. (2017) · BMC Cardiovascular Disorders · doi:10.1186/s12872-017-0557-7 · Cited by 11
“The device firmware transforms these impulses and summarises them over discrete epochs into counts per time interval [31].”
Method
From Steps to Context: Optimizing Digital Phenotyping for Physical Activity Monitoring in Older Adults by Integrating Wearable Data and Ecological Momentary Assessment
Daniels, K., Quadflieg, K., Robijns, J., Vry, J. D., Alphen, H. V., Beers, R. V., Sourbron, B., Vanbuel, A., Meekers, S., Mattheeussen, M., et al. (2025) · Sensors · doi:10.3390/s25030858 · Cited by 12
“The two-week period was chosen based on existing literature on EMA [33,44,45] and PA monitoring [46–49] with wearables, which indicates that at least four to seven days are required to capture variability in daily behaviors, including both weekdays and weekends.”
A comparison of accelerometer cut-points for measuring physical activity and sedentary time in adolescents with Down syndrome
Forseth, B. M., Carlson, J., Willis, E. A., Helsel, B. C., & Ptomey, L. T. (2021) · Research in Developmental Disabilities · doi:10.1016/j.ridd.2021.104126 · Cited by 10
Assessment of the MyWellness Key accelerometer in people with type 2 diabetes
McGinley, S. K., Armstrong, M. J., Khandwala, F., Zanuso, S., & Sigal, R. J. (2015) · Applied Physiology Nutrition and Metabolism · doi:10.1139/apnm-2015-0169 · Cited by 10
“movement and can categorize movement into light, moderate, and vigorous intensities (Butte et al. 2012; Strath et al. 2013).”
Background
Clinicians and individuals with acquired brain injury perspectives about factors that influence mobility: creating a core set of mobility domains among individuals with acquired brain injury
Alhasani, R., Radman, D. P., Auger, C., Lamontagne, A., & Ahmed, S. (2021) · Annals of Medicine · doi:10.1080/07853890.2021.2015539 · Cited by 9
Reliable and developmentally appropriate study end points are needed to achieve drug development for treatment of pediatric pulmonary arterial hypertension
Sun, H., Stockbridge, N., Ariagno, R. L., Murphy, D., Nelson, R. M., & Rodriguez, W. J. (2016) · Journal of Perinatology · doi:10.1038/jp.2016.103 · Cited by 10
Comparing Real-Time Self-Tracking and Device-Recorded Exercise Data in Subjects with Type 1 Diabetes
Groat, D., Kwon, H.-R., Grando, M., Cook, C., & Thompson, B. M. (2018) · Applied Clinical Informatics · doi:10.1055/s-0038-1676458 · Cited by 10
“16 20 Although it has been suggested that combining methods to measure exercise in real-life outpatient settings may be the best way to accurately assess periods of exercise, this approach remains understudied.”
Accuracy and reliability of accelerometer-based pedometers in step counts during walking, running, and stair climbing in different locations of attachment
Pan, J., & Wei, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-78684-w · Cited by 10
Physical activity after cardiac arrest; protocol of a sub-study in the Targeted Hypothermia versus Targeted Normothermia after Out-of-Hospital Cardiac Arrest trial (TTM2)
Heimburg, K., Lilja, G., Tornberg, Å. B., Ullén, S., Nordström, E., Friberg, H., Nielsen, N., Oestergaard, L. G., Grejs, A. M., Hill, H., et al. (2021) · Resuscitation Plus · doi:10.1016/j.resplu.2021.100076 · Cited by 9
In Situ Approaches to Studying Occupants
O’Brien, W., Gilani, S., & Gunay, B. (2017) · Springer eBooks · doi:10.1007/978-3-319-61464-9_6 · Cited by 9
Comparison and calibration of 24‐hour physical activity recall in adult population
Borges, L. P. S. L., Ries, D., Sousa, A. G., & da Costa, T. H. M. (2020) · European Journal of Sport Science · doi:10.1080/17461391.2020.1866077 · Cited by 9
Objectively Measured Physical Activity in Home Guard Soldiers During Military Service and Civilian Life
Aandstad, A., Hageberg, R., Holme, I., & Anderssen, S. A. (2016) · Military Medicine · doi:10.7205/milmed-d-15-00147 · Cited by 9
“However, comparing PA values from different studies might be limited by several factors, such as the use of different PA monitors or different data processing methods.(21) We have identified some civilian studies which used the same monitor as in our study, but comparisons to our data might still be difficult since di…”
Result
Monitoring Sleep and Nightly Recovery with Wrist-Worn Wearables: Links to Training Load and Performance Adaptations
Nuuttila, O., Olstad, D. S., Martinmäki, K., Uusitalo, A. L. T., & Kyröläinen, H. (2025) · Sensors · doi:10.3390/s25020533 · Cited by 9
Effectiveness of digital behaviour change interventions for promoting physical activity in adolescents with overweight and obesity: A systematic review and meta-analysis
Kassim, P. S. J., Muhammad, N. A., Rahman, N. F. A., Sidik, S. M., Essau, C. A., & Shah, S. A. (2025) · Digital Health · doi:10.1177/20552076251314904 · Cited by 9
“31 These devices could capture various aspects of physical activity, such as minutes spent in MVPA, steps per day or metabolic equivalence of task (MET) hours.”
Modeling Clinically Validated Physical Activity Assessments Using Commodity Hardware
Winfree, K. N., & Dominick, G. M. (2017) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2017.2787461 · Cited by 8
Comparison of association between physical activity and resting metabolic rate in young and middle-aged Korean adults
Hwang, H., Jung, W., Kim, J., Park, H., & Lim, K. (2019) · Physical Activity and Nutrition · doi:10.20463/jenb.2019.0012 · Cited by 9
Changes in Physical Activity and Sleep Among Veterans Using a Service Dog as a Rehabilitation Modality for Post-traumatic Stress Disorder: An Open-Label Single-Arm Exploratory Trial Using Actigraphy-Based Measures
Lessard, G., Gagnon, D. H., & Vincent, C. (2020) · Journal of Psychosocial Rehabilitation and Mental Health · doi:10.1007/s40737-020-00187-4 · Cited by 8
Requirements and Architecture of a Cloud Based Insomnia Therapy and Diagnosis Platform: A Smart Cities Approach
Reichenpfader, D., & Hanke, S. (2021) · Smart Cities · doi:10.3390/smartcities4040070 · Cited by 8

Authors: BUTTE, N. F., EKELUND, U., & WESTERTERP, K. R.
Affiliations: Agricultural Research Service (US)
University of Cambridge (GB)
Maastricht University (NL)
ORCID: BUTTE, NANCY F.
EKELUND, ULF
WESTERTERP, KLAAS R.
Venue: Medicine & Science in Sports & Exercise
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2012-01
Volume: 44
Issue: 1S
Pages: S5-S12
ISSN: 0195-9131 (ISSN-L)
DOI: 10.1249/mss.0b013e3182399c0e
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: green
cris.maastrichtuniversity.nl
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

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Assessing Physical Activity Using Wearable Monitors: Measures of Physical Activity

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