Cited by 996Physical Activity and HealthContext-Aware Activity Recognition SystemsObesity, Physical Activity, Diet

The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.

The Technology of Accelerometry-Based Activity Monitors: Current and Future

CHEN, KONG Y., BASSETT, DAVID R.·2005·Medicine & Science in Sports & Exercise

Open this paper in CoChat — free account

Abstract

PURPOSE: This paper reviews accelerometry-based activity monitors, including single-site first-generation devices, emerging technologies, and analytical approaches to predict energy expenditure, with suggestions for further research and development. METHODS: The physics and measurement principles of the accelerometer are described, including the sensor properties, data collections, filtering, and integration analyses. The paper also compares these properties in several commonly used single-site accelerometers. The emerging accelerometry technologies introduced include the multisensor arrays and the combination of accelerometers with physiological sensors. The outputs of accelerometers are compared with criterion measures of energy expenditure (indirect calorimeters and double-labeled water) to develop mathematical models (linear, nonlinear, and variability approaches). RESULTS: The technologies of the sensor and data processing directly influence the results of the outcome measurement (activity counts and energy expenditure predictions). Multisite assessment and combining accelerometers with physiological measures may offer additional advantages. Nonlinear approaches to predict energy expenditure using accelerometer outputs from multiple sites and orientation can enhance accuracy. CONCLUSIONS: The development of portable accelerometers has made objective assessments of physical activity possible. Future technological improvements will include examining raw acceleration signals and developing advanced models for accurate energy expenditure predictions.

Integrity signals

Registry

Crossref · 10.1249/01.mss.0000185571.49104.82

Cites

61 of 61 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?

Healthy People 2010
Yu, S. M. (1998) · Maternal and Child Health Journal · doi:10.1023/a:1021801927353 · Cited by 3,876
Calibration of the Computer Science and Applications, Inc. accelerometer
FREEDSON, P. S., MELANSON, E., & SIRARD, J. (1998) · Medicine & Science in Sports & Exercise · doi:10.1097/00005768-199805000-00021 · Cited by 3,825
Medical Instrumentation-Application and Design
Webster, J. G. (1978) · Journal of Clinical Engineering · doi:10.1097/00004669-197807000-00017 · Cited by 1,846
Calibration of Accelerometer Output for Children
Freedson, P. S., POBER, D. M., & Janz, K. F. (2005) · Medicine & Science in Sports & Exercise · doi:10.1249/01.mss.0000185658.28284.ba · Cited by 1,150
Energy expenditure by doubly labeled water: validation in humans and proposed calculation
Schoeller, D. A., Ravussin, É., Schutz, Y., Acheson, K. J., Baertschi, P., & Jéquier, E. (1986) · American Journal of Physiology-Regulatory, Integrative and Comparative Physiology · doi:10.1152/ajpregu.1986.250.5.r823 · Cited by 683
Calibration of Accelerometer Output for Adults
MATTHEW, C. E. (2005) · Medicine & Science in Sports & Exercise · doi:10.1249/01.mss.0000185659.11982.3d · Cited by 651
Validity of heart rate, pedometry, and accelerometry for predicting the energy cost of children’s activities
Eston, R. G., Rowlands, A. V., & Ingledew, D. K. (1998) · Journal of Applied Physiology · doi:10.1152/jappl.1998.84.1.362 · Cited by 643
Validity of four motion sensors in measuring moderate intensity physical activity
Bassett, D. R. (2000) · Medicine & Science in Sports & Exercise · doi:10.1097/00005768-200009001-00006 · Cited by 533
Self-citation
Validity of accelerometry for the assessment of moderate intensity physical activity in the field
HENDELMAN, D., MILLER, K., BAGGETT, C., DEBOLD, E., & FREEDSON, P. (2000) · Medicine & Science in Sports & Exercise · doi:10.1097/00005768-200009001-00002 · Cited by 516
Estimation of energy expenditure using CSA accelerometers at hip and wrist sites
Swartz, A. M., Strath, S. J., Bassett, D. R., BRIEN, W. L. O., King, G. A., & Ainsworth, B. E. (2000) · Medicine & Science in Sports & Exercise · doi:10.1097/00005768-200009001-00003 · Cited by 514
Self-citation

Show all 61 references

Sorted by citations

Items 101–200 of 994

Wearable Systems for Monitoring Mobility-Related Activities in Chronic Disease: A Systematic Review
Allet, L., Knols, R. H., Shirato, K., & de Bruin, E. D. (2010) · Sensors · doi:10.3390/s101009026 · Cited by 118
Estimating Absolute and Relative Physical Activity Intensity Across Age via Accelerometry in Adults
Miller, N. E., Strath, S. J., Swartz, A. M., & Cashin, S. E. (2010) · Journal of Aging and Physical Activity · doi:10.1123/japa.18.2.158 · Cited by 117
New Horizons in Sensor Development
Intille, S. S., Lester, J., Sallis, J. F., & Duncan, G. E. (2011) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e3182399c7d · Cited by 116
Identifying waking time in 24-h accelerometry data in adults using an automated algorithm
van der Berg, J. D., Willems, P. J. B., van der Velde, J. H. P. M., Savelberg, H. H. C. M., Schaper, N. C., Schram, M. T., Sep, S. J. S., Dagnelie, P. C., Bosma, H., Stehouwer, C. D. A., et al. (2016) · Journal of Sports Sciences · doi:10.1080/02640414.2016.1140908 · Cited by 112
Comparison of the ActiGraph 7164 and the ActiGraph GT1M during Self-Paced Locomotion
Keadle, S. K., STAUDENMAYER, J. W., Troiano, R. P., & Freedson, P. S. (2010) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e3181c29e90 · Cited by 113
Validity of self-reported total physical activity questionnaire among older women
Orsini, N., Bellocco, R., Bottai, M., Hagströmer, M., Sjöstróm, M., Pagano, M., & Wolk, A. (2008) · European Journal of Epidemiology · doi:10.1007/s10654-008-9273-z · Cited by 111
Body Posture Identification using Hidden Markov Model with a Wearable Sensor Network
Quwaider, M., & Biswas, S. K. (2008) · International Conference on Body Area Networks · doi:10.4108/icst.bodynets2008.2932 · Cited by 107
Calibration of raw accelerometer data to measure physical activity: A systematic review
Mendes, M. D. A., Crochemore‐Silva, I., Ramires, V. V., Reichert, F. F., Martins, R. C., & Tomasi, E. (2017) · Gait & Posture · doi:10.1016/j.gaitpost.2017.12.028 · Cited by 109
A Real-Time and Self-Calibrating Algorithm Based on Triaxial Accelerometer Signals for the Detection of Human Posture and Activity
Curone, D., Bertolotti, G. M., Cristiani, A., Secco, E. L., & Magenes, G. (2010) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2010.2050696 · Cited by 105
Tracking human activity and well-being in natural environments using wearable sensors and experience sampling
Doherty, S. T., Lemieux, C. J., & Canally, C. (2014) · Social Science & Medicine · doi:10.1016/j.socscimed.2014.01.048 · Cited by 110
Physical Activities Monitoring Using Wearable Acceleration Sensors Attached to the Body
Arif, M., & Kattan, A. J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0130851 · Cited by 105
Estimation of Free‐Living Energy Expenditure Using a Novel Activity Monitor Designed to Minimize Obtrusiveness
Bonomi, A. G., Plasqui, G., Goris, A. H. C., & Westerterp, K. R. (2010) · Obesity · doi:10.1038/oby.2010.34 · Cited by 100
Changes in Daily Activity Patterns with Age in U.S. Men and Women: National Health and Nutrition Examination Survey 2003–04 and 2005–06
Martin, K. R., Koster, A., Murphy, R. A., Domelen, D. R. V., Hung, M., Brychta, R. J., Chen, K. Y., & Harris, T. B. (2014) · Journal of the American Geriatrics Society · doi:10.1111/jgs.12893 · Cited by 98
Self-citation
Physical Activity and Dietary Behavior in US Adults and Their Combined Influence on Health
Loprinzi, P. D., Smit, E., & Mahoney, S. E. (2014) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2013.09.018 · Cited by 100
Physical Activity Levels and Patterns of 19-Month-Old Children
Hnatiuk, J. A., Ridgers, N. D., Salmon, J., Campbell, K. J., McCallum, Z., & Hesketh, K. D. (2012) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e31825825c4 · Cited by 99
Physical activity using wrist‐worn accelerometers: comparison of dominant and non‐dominant wrist
Dieu, O., Mikulovic, J., Fardy, P. S., Bui-Xuân, G., Béghin, L., & Vanhelst, J. (2016) · Clinical Physiology and Functional Imaging · doi:10.1111/cpf.12337 · Cited by 99
Assessment of Physical Activity in Adults Using Wrist Accelerometers
Liu, F., Wanigatunga, A. A., & Schrack, J. A. (2021) · Epidemiologic Reviews · doi:10.1093/epirev/mxab004 · Cited by 110
Patient-centered Outcomes Research in Interstitial Lung Disease: An Official American Thoracic Society Research Statement
Aronson, K. I., Danoff, S. K., Russell, A., Ryerson, C. J., Suzuki, A., Wijsenbeek, M. S., Bajwah, S., Bianchi, P., Corte, T. J., Lee, J. S., et al. (2021) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.202105-1193st · Cited by 102
Assessment tools in obesity — Psychological measures, diet, activity, and body composition
Beechy, L., Galpern, J., Petrone, A. B., & Das, S. K. (2012) · Physiology & Behavior · doi:10.1016/j.physbeh.2012.04.013 · Cited by 117
Better Physical Activity Classification using Smartphone Acceleration Sensor
Arif, M., Bilal, M., Kattan, A. J., & Ahamed, S. I. (2014) · Journal of Medical Systems · doi:10.1007/s10916-014-0095-0 · Cited by 99
ActiGraph GT3X+ and Actical Wrist and Hip Worn Accelerometers for Sleep and Wake Indices in Young Children Using an Automated Algorithm: Validation With Polysomnography
Smith, C. P., Galland, B. C., Taylor, R. W., & Meredith-Jones, K. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00958 · Cited by 93
Ambulatory Activity Monitoring
Bussmann, J. B. J., Ebner‐Priemer, U., & Fahrenberg, J. (2009) · European Psychologist · doi:10.1027/1016-9040.14.2.142 · Cited by 95
The Role of Emergent Technologies in the Dynamic and Kinematic Assessment of Human Movement in Sport and Clinical Applications
Edriss, S., Romagnoli, C., Caprioli, L., Zanela, A., Panichi, E., Campoli, F., Padua, E., Annino, G., & Bonaiuto, V. (2024) · Applied Sciences · doi:10.3390/app14031012 · Cited by 94
Validity of physical activity monitors for assessing lower intensity activity in adults
Calabr, M. A. S., Lee, J. M., Saint‐Maurice, P. F., Yoo, H., & Welk, G. J. (2014) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-014-0119-7 · Cited by 93
High Resolution MEMS Accelerometers to Estimate VO2 and Compare Running Mechanics between Highly Trained Inter-Collegiate and Untrained Runners
McGregor, S. J., Busa, M. A., Yaggie, J. A., & Bollt, E. M. (2009) · PLoS ONE · doi:10.1371/journal.pone.0007355 · Cited by 92
Validity of an upper-body-mounted accelerometer to measure peak vertical and resultant force during running and change-of-direction tasks
Wundersitz, D. W. T., Netto, K., Aisbett, B., & Gastin, P. B. (2013) · Sports Biomechanics · doi:10.1080/14763141.2013.811284 · Cited by 91
Validity of the ActiGraph GT1M during walking and cycling
Hansen, B. H., Børtnes, I., Hildebrand, M., Holme, I., Kolle, E., & Anderssen, S. A. (2013) · Journal of Sports Sciences · doi:10.1080/02640414.2013.844347 · Cited by 90
Total Activity Counts and Bouted Minutes of Moderate-To-Vigorous Physical Activity: Relationships With Cardiometabolic Biomarkers Using 2003–2006 NHANES
Wolff‐Hughes, D. L., Fitzhugh, E. C., Bassett, D. R., & Churilla, J. R. (2014) · Journal of Physical Activity and Health · doi:10.1123/jpah.2013-0463 · Cited by 89
Self-citation
Assessing physical behavior through accelerometry – State of the science, best practices and future directions
Burchartz, A., Anedda, B., Auerswald, T., Giurgiu, M., Hill, H., Ketelhut, S., Kolb, S., Mall, C., Manz, K., Nigg, C. R., et al. (2020) · Psychology of sport and exercise · doi:10.1016/j.psychsport.2020.101703 · Cited by 104
A guide to assessing physical activity using accelerometry in cancer patients
Broderick, J. M., Ryan, J. M., O’Donnell, D. M., & Hussey, J. M. (2014) · Supportive Care in Cancer · doi:10.1007/s00520-013-2102-2 · Cited by 92
Objective monitoring of physical activity in children: considerations for instrument selection
McClain, J. J., & Tudor‐Locke, C. (2008) · Journal of science and medicine in sport · doi:10.1016/j.jsams.2008.09.012 · Cited by 88
Physical activity and energy expenditure measurements using accelerometers in older adults.
Garatachea, N., Luque, G. T., & González‐Gallego, J. (2010) · PubMed · Cited by 87
Association of change in brain structure to objectively measured physical activity and sedentary behavior in older adults: Age, Gene/Environment Susceptibility-Reykjavik Study
Arnardottir, N. Y., Koster, A., Domelen, D. R. V., Brychta, R. J., Caserotti, P., Eiríksdóttir, G., Sverrisdottir, J. E., Sigurdsson, S. O., Jóhannsson, E., Chen, K. Y., et al. (2015) · Behavioural Brain Research · doi:10.1016/j.bbr.2015.09.005 · Cited by 92
Self-citation
Assessing free‐living physical activity using accelerometry: Practical issues for researchers and practitioners
Ridgers, N. D., & Fairclough, S. J. (2011) · European Journal of Sport Science · doi:10.1080/17461391.2010.501116 · Cited by 86
Estimating Activity‐related Energy Expenditure Under Sedentary Conditions Using a Tri‐axial Seismic Accelerometer
van Hees, V. T., van Lummel, R. C., & Westerterp, K. R. (2009) · Obesity · doi:10.1038/oby.2009.55 · Cited by 85
Advances in physical activity monitoring and lifestyle interventions in obesity: a review
Bonomi, A. G., & Westerterp, K. R. (2011) · International Journal of Obesity · doi:10.1038/ijo.2011.99 · Cited by 85
The Relationship Between Hispanic Parents and Their Preschool-Aged Children's Physical Activity
Ruiz, R. M., Gesell, S. B., Buchowski, M. S., Lambert, W. E., & Barkin, S. L. (2011) · PEDIATRICS · doi:10.1542/peds.2010-1712 · Cited by 93
Sensors Capabilities, Performance, and Use of Consumer Sleep Technology
de Zambotti, M., Cellini, N., Menghini, L., Sarlo, M., & Baker, F. C. (2020) · Sleep Medicine Clinics · doi:10.1016/j.jsmc.2019.11.003 · Cited by 95
Using Sensors to Measure Activity in People with Stroke
Fulk, G. D., & Sazonov, E. E. (2011) · Topics in Stroke Rehabilitation · doi:10.1310/tsr1806-746 · Cited by 83
Short-Term Effectiveness of a Mobile Phone App for Increasing Physical Activity and Adherence to the Mediterranean Diet in Primary Care: A Randomized Controlled Trial (EVIDENT II Study)
Recio-Rodriguez, J. I., Agudo-Conde, C., Martin-Cantera, C., González-Viejo, M. N., Fernandez-Alonso, M. D. C., Arietaleanizbeaskoa, M. S., Schmolling-Guinovart, Y., Maderuelo-Fernandez, J.-A., Rodriguez-Sanchez, E., Gomez-Marcos, M. A., et al. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.6814 · Cited by 82
Number of days required to estimate physical activity constructs objectively measured in different age groups: Findings from three Brazilian (Pelotas) population-based birth cohorts
Ricardo, L. I. C., Wendt, A. T., Galliano, L. M., Müller, W. D. A., Cruz, G. I. N., Wehrmeister, F. C., Brage, S., Ekelund, U., & Crochemore‐Silva, I. (2020) · PLoS ONE · doi:10.1371/journal.pone.0216017 · Cited by 85
How Do Neighbourhood Definitions Influence the Associations between Built Environment and Physical Activity?
Mavoa, S., Bagheri, N., Koohsari, M., Kaczynski, A., Lamb, K., Oka, K., O’Sullivan, D., & Witten, K. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16091501 · Cited by 64
An evaluation of wearable activity monitoring devices
Guo, F., Li, Y., Kankanhalli, M. S., & Brown, M. S. (2013) · Proceedings of the 1st ACM international workshop on Personal data meets distributed multimedia · doi:10.1145/2509352.2512882 · Cited by 80
Reliability and Validity of the International Physical Activity Questionnaire for Assessing Walking
van der Ploeg, H. P., Tudor‐Locke, C., Marshall, A. L., Craig, C. L., Hagströmer, M., Sjöstróm, M., & Bauman, A. E. (2010) · Research Quarterly for Exercise and Sport · doi:10.1080/02701367.2010.10599632 · Cited by 81
Physical Activity and Health
Hills, A. P., Street, S. J., & Byrne, N. M. (2015) · Advances in food and nutrition research · doi:10.1016/bs.afnr.2015.06.001 · Cited by 88
Algorithms for using an activity-based accelerometer for identification of infant sleep–wake states during nap studies
Galland, B. C., Kennedy, G., Mitchell, E. A., & Taylor, B. J. (2012) · Sleep Medicine · doi:10.1016/j.sleep.2012.01.018 · Cited by 80
The impact of “home office” work on physical activity and sedentary behavior during the COVID-19 pandemic: a systematic review
Wilms, P., Schröder, J., Reer, R., & Scheit, L. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph191912344 · Cited by 79
Field based reliability and validity of the bioharness™ multivariable monitoring device.
Johnstone, J., Ford, P. A., Hughes, G., Watson, T., Mitchell, A., & Garrett, A. T. (2012) · Europe PMC (PubMed Central) · Cited by 85
Triaxial Accelerometry for Assessment of Physical Activity in Young Children
Tanaka, C., Tanaka, S., Kawahara, J., & Midorikawa, T. (2007) · Obesity · doi:10.1038/oby.2007.145 · Cited by 77
A comparison of the Actigraph GT1M and GT3X accelerometers under standardized and free-living conditions
Kaminsky, L. A., & Ozemek, C. (2012) · Physiological Measurement · doi:10.1088/0967-3334/33/11/1869 · Cited by 79
Usability of a Medication Event Reminder Monitor System (MERM) by Providers and Patients to Improve Adherence in the Management of Tuberculosis
Liu, X., Blaschke, T. F., Thomas, B. V., Geest, S. D., Jiang, S., Gao, Y., Li, X., Buono, E. W., Buchanan, S., Zhang, Z., et al. (2017) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph14101115 · Cited by 78
Bioharness(™) Multivariable Monitoring Device: Part. II: Reliability.
Johnstone, J., Ford, P. A., Hughes, G., Watson, T., & Garrett, A. T. (2012) · Europe PMC (PubMed Central) · Cited by 78
Accelerometer Prediction of Energy Expenditure
Howe, C. A., STAUDENMAYER, J. W., & Freedson, P. S. (2009) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e3181aa3a0e · Cited by 78
Computational Methods for Estimating Energy Expenditure in Human Physical Activities
LIU, S., Gao, R. X., & Freedson, P. S. (2012) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e31825e825a · Cited by 78
Concurrent validity of the Fitbit for assessing sedentary behavior and moderate-to-vigorous physical activity
Redenius, N., Kim, Y., & Byun, W. (2019) · BMC Medical Research Methodology · doi:10.1186/s12874-019-0668-1 · Cited by 80
Population-Referenced Percentiles for Waist-Worn Accelerometer-Derived Total Activity Counts in U.S. Youth: 2003 – 2006 NHANES
Wolff‐Hughes, D. L., Bassett, D. R., & Fitzhugh, E. C. (2014) · PLoS ONE · doi:10.1371/journal.pone.0115915 · Cited by 75
Self-citation
Intermonitor Variability of GT3X Accelerometer
Santos‐Lozano, A., Torres‐Luque, G., Marin, P. J., Ruiz, J. R., Lucía, A., & Garatachea, N. (2012) · International Journal of Sports Medicine · doi:10.1055/s-0032-1312580 · Cited by 76
Healthy Lifestyle Characteristics and Their Joint Association With Cardiovascular Disease Biomarkers in US Adults
Loprinzi, P. D., Branscum, A. J., Hanks, J. E., & Smit, E. (2016) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2016.01.009 · Cited by 76
Accelerometer-Assessed Physical Activity and Sedentary Time in Youth With Disabilities
Lobenius-Palmér, K., Nätterlund, B., Hurtig‐Wennlöf, A., & Lundqvist, L. (2017) · Adapted Physical Activity Quarterly · doi:10.1123/apaq.2015-0065 · Cited by 82
Physical activity levels in adults and elderly from triaxial and uniaxial accelerometry. The Tromsø Study
Sagelv, E. H., Ekelund, U., Pedersen, S., Brage, S., Hansen, B. H., Johansson, J., Grimsgaard, S., Nordström, A., Horsch, A., Hopstock, L. A., et al. (2019) · PLoS ONE · doi:10.1371/journal.pone.0225670 · Cited by 77
A comparison of energy expenditure estimates from the Actiheart and Actical physical activity monitors during low intensity activities, walking, and jogging
Spierer, D. K., Hagins, M., Rundle, A., & Pappas, E. (2010) · European Journal of Applied Physiology · doi:10.1007/s00421-010-1672-7 · Cited by 73
Wearables for Promoting Physical Activity
Strath, S. J., & Rowley, T. W. (2017) · Clinical Chemistry · doi:10.1373/clinchem.2017.272369 · Cited by 74
Validation of Cross-Sectional Time Series and Multivariate Adaptive Regression Splines Models for the Prediction of Energy Expenditure in Children and Adolescents Using Doubly Labeled Water ,
Butte, N. F., Wong, W. W., Adolph, A. L., Puyau, M. R., Vohra, F. A., & Zakeri, I. (2010) · Journal of Nutrition · doi:10.3945/jn.109.120162 · Cited by 77
When cities move children: Development of a new methodology to assess context-specific physical activity behaviour among children and adolescents using accelerometers and GPS
Klinker, C. D., Schipperijn, J., Toftager, M., Kerr, J., & Troelsen, J. (2014) · Health & Place · doi:10.1016/j.healthplace.2014.11.006 · Cited by 73
The Distribution of Physical Activity in an After-school Friendship Network
Gesell, S. B., Tesdahl, E. A., & Ruchman, E. (2012) · PEDIATRICS · doi:10.1542/peds.2011-2567 · Cited by 80
Assessing Physical Activity as a Core Component in Cardiac Rehabilitation
Kaminsky, L. A., Brubaker, P. H., Guazzi, M., Lavie, C. J., Montoye, A. H. K., Sanderson, B., & Savage, P. D. (2016) · Journal of Cardiopulmonary Rehabilitation and Prevention · doi:10.1097/hcr.0000000000000191 · Cited by 76
Association of Physical Activity and Sedentary Behavior with Biological Markers Among U.S. Pregnant Women
Loprinzi, P. D., Fitzgerald, E. M., Woekel, E., & Cardinal, B. J. (2013) · Journal of Women s Health · doi:10.1089/jwh.2013.4394 · Cited by 71
Comparison of uniaxial and triaxial accelerometry in the assessment of physical activity among adolescents under free-living conditions: the HELENA study
Vanhelst, J., Béghin, L., Duhamel, A., Bergman, P., Sjöstróm, M., & Gottrand, F. (2012) · BMC Medical Research Methodology · doi:10.1186/1471-2288-12-26 · Cited by 72
Reproducibility of a Triaxial Seismic Accelerometer (DynaPort)
van Hees, V. T., Slootmaker, S. M., GROOT, G. D., van Mechelen, W., & van Lummel, R. C. (2009) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e31818ff636 · Cited by 71
Concurrent validity of the PAM accelerometer relative to the MTI Actigraph using oxygen consumption as a reference
Slootmaker, S. M., Chin A Paw, M. J. M., Schuit, A. J., Van Mechelen, W., & Koppes, L. L. J. (2009) · Scandinavian Journal of Medicine & Science in Sports · doi:10.1111/j.1600-0838.2007.00740.x · Cited by 69
Challenges and Emerging Technologies within the Field of Pediatric Actigraphy
Galland, B. C., Meredith-Jones, K., Terrill, P. I., & Taylor, R. W. (2014) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2014.00099 · Cited by 69
Free-living energy expenditure in children using multi-sensor activity monitors
Arvidsson, D., Slinde, F., & Hulthén, L. (2009) · Clinical Nutrition · doi:10.1016/j.clnu.2009.03.006 · Cited by 69
Resting-State Functional Connectivity and Its Association With Multiple Domains of Upper-Extremity Function in Chronic Stroke
Urbin, M. A., Hong, X., Lang, C. E., & Carter, A. R. (2014) · Neurorehabilitation and neural repair · doi:10.1177/1545968314522349 · Cited by 68
Reliability and Validity of Objective Measures of Physical Activity in Youth With Cerebral Palsy Who Are Ambulatory
O’Neil, M. E., Fragala-Pinkham, M. A., Lennon, N., George, A., Forman, J., & Trost, S. G. (2015) · Physical Therapy · doi:10.2522/ptj.20140201 · Cited by 69
Leg Motion Classification with Artificial Neural Networks Using Wavelet-Based Features of Gyroscope Signals
Ayrulu, B., & Barshan, B. (2011) · Sensors · doi:10.3390/s110201721 · Cited by 68
Validity of a Multisensor Armband in Estimating 24-h Energy Expenditure in Children
Dorminy, C. A., Choi, L., Akohoue, S. A., Chen, K. Y., & Buchowski, M. S. (2008) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e318161ea8f · Cited by 66
Self-citation
Validation of the Actical Activity Monitor in Middle-Aged and Older Adults
Hooker, S. P., Feeney, A., Hutto, B., Pfeiffer, K. A., McIver, K. L., Heil, D. P., Vena, J. E., LaMonte, M. J., & Blair, S. N. (2011) · Journal of Physical Activity and Health · doi:10.1123/jpah.8.3.372 · Cited by 66
Accelerometer data requirements for reliable estimation of habitual physical activity and sedentary time of children during the early years - a worked example following a stepped approach
Bingham, D. D., Costa, S., Clemes, S. A., Routen, A. C., Moore, H. J., & Barber, S. (2016) · Journal of Sports Sciences · doi:10.1080/02640414.2016.1149605 · Cited by 73
Walking and Measurement
Bassett, D. R., Mahar, M. T., Rowe, D. A., & Morrow, J. R. (2008) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e31817c699c · Cited by 65
Self-citation
Classification Accuracy of the Wrist-Worn Gravity Estimator of Normal Everyday Activity Accelerometer
Welch, W. A., Bassett, D. R., Thompson, D. L., Freedson, P. S., STAUDENMAYER, J. W., John, D., Steeves, J. A., Conger, S. A., CEASER, T. G., Howe, C. A., et al. (2013) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e3182965249 · Cited by 67
Self-citation
Relative Validity of 3 Accelerometer Models for Estimating Energy Expenditure During Light Activity
Wetten, A. A., Batterham, M. J., Tan, S., & Tapsell, L. C. (2014) · Journal of Physical Activity and Health · doi:10.1123/jpah.2011-0167 · Cited by 70
An intelligent driver location system for smart parking
Lan, K.-C., & Shih, W.-Y. (2013) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.09.044 · Cited by 65
No differences in physical activity in (un)diagnosed asthma and healthy controls
van Gent, R., van der Ent, C. K., van Essen‐Zandvliet, L. E. M., Rovers, M. M., Kimpen, J. L. L., de Meer, G., & Klijn, P. H. C. (2007) · Pediatric Pulmonology · doi:10.1002/ppul.20672 · Cited by 65
Effectiveness of a smartphone application for improving healthy lifestyles, a randomized clinical trial (EVIDENT II): study protocol
Recio-Rodriguez, J. I., Martín-Cantera, C., González-Viejo, N., Gómez-Arranz, A., Arietaleanizbeaskoa, M. S., Schmolling-Guinovart, Y., Maderuelo-Fernández, J. Á., Pérez-Arechaederra, D., Rodríguez‐Sánchez, E., Gómez-Marcos, M. Á., et al. (2014) · BMC Public Health · doi:10.1186/1471-2458-14-254 · Cited by 69
Rates and Determinants of Uptake and Use of an Internet Physical Activity and Weight Management Program in Office and Manufacturing Work Sites in England: Cohort Study
Ware, L. J., Hurling, R., Bataveljic, O., Fairley, B. W., HURST, T. L., Murray, P., Rennie, K. L., Tomkins, C. E., Finn, A., Cobain, M. R., et al. (2008) · Journal of Medical Internet Research · doi:10.2196/jmir.1108 · Cited by 65
Dietary Intakes and Physical Activity among Preschool-Aged Children Living in Rural American Indian Communities before a Family-Based Healthy Lifestyle Intervention
LaRowe, T. L., Adams, A., Jobe, J. B., Cronin, K. A., Vannatter, S. M., & Prince, R. J. (2010) · Journal of the American Dietetic Association · doi:10.1016/j.jada.2010.04.009 · Cited by 63
Accuracy of inclinometer functions of the activPAL and ActiGraph GT3X+: A focus on physical activity
An, H.-S., Kim, Y., & Lee, J. M. (2016) · Gait & Posture · doi:10.1016/j.gaitpost.2016.10.014 · Cited by 62
Actigraphic Measurement of Motor Deficits in Acute Ischemic Stroke
Gebruers, N., Truijen, S., Engelborghs, S., Nagels, G., Brouns, R., & De Deyn, P. P. (2008) · Cerebrovascular Diseases · doi:10.1159/000160210 · Cited by 61
Identifying Sheep Activity from Tri-Axial Acceleration Signals Using a Moving Window Classification Model
Barwick, J., Lamb, D. W., Dobos, R. C., Welch, M., Schneider, D. A., & Trotter, M. G. (2020) · Remote Sensing · doi:10.3390/rs12040646 · Cited by 62
Self-Reported Physical Activity in Hispanic Adults Living With HIV: Comparison With Accelerometer and Pedometer
Ramírez-Marrero, F. A., Rivera‐Brown, A. M., Nazario, C. M., Rodríguez‐Orengo, J. F., Smit, E., & Smith, B. A. (2008) · Journal of the Association of Nurses in AIDS Care · doi:10.1016/j.jana.2008.04.003 · Cited by 58
A comparison of physical activity (PA) assessment tools across levels of frailty
Theou, O., Jakobi, J. M., Vandervoort, A. A., & Jones, G. R. (2011) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2011.12.005 · Cited by 62
Sedentary and Physical Activity Patterns in Adults with Intellectual Disability
Oviedo, G. R., Travier, N., & Guerra-Balic, M. (2017) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph14091027 · Cited by 75
An evaluation of wearable sensors and their placements for analyzing construction worker's trunk posture in laboratory conditions
Lee, W., Seto, E., Lin, K., & Migliaccio, G. C. (2017) · Applied Ergonomics · doi:10.1016/j.apergo.2017.03.016 · Cited by 62
Assessing the effects of sampling frequency on behavioural classification of accelerometer data
Hounslow, J. L., Brewster, L. R., Lear, K. O., Guttridge, T. L., Daly, R., Whitney, N. M., & Gleiss, A. C. (2019) · Journal of Experimental Marine Biology and Ecology · doi:10.1016/j.jembe.2018.12.003 · Cited by 61
Validity of the ActivPAL™ and the ActiGraph Monitors in Preschoolers
Decker, E. D., Craemer, M. D., Santos‐Lozano, A., Cauwenberghe, E. V., Bourdeaudhuij, I. D., & Cardon, G. (2013) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e318292c575 · Cited by 62
Technical Reliability Assessment of the Actigraph GT1M Accelerometer
Silva, P., Mota, J. A. P. S., Esliger, D., & Welk, G. J. (2010) · Measurement in Physical Education and Exercise Science · doi:10.1080/10913671003715524 · Cited by 59
Using smart-phones and floor plans for indoor location tracking
Lan, K.-C., & Shih, W.-Y. (2014) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2013.2296875 · Cited by 59
Measurement of Dynamical Resilience Indicators Improves the Prediction of Recovery Following Hospitalization in Older Adults
Gijzel, S. M. W., Rector, J. L., van Meulen, F., van der Loeff, R. S., van de Leemput, I. A., Scheffer, M., Rikkert, M. G. M. O., & Melis, R. J. F. (2019) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2019.10.011 · Cited by 58
On Calibrating the Sensor Errors of a PDR-Based Indoor Localization System
Lan, K.-C., & Shih, W.-Y. (2013) · Sensors · doi:10.3390/s130404781 · Cited by 59
Prediction of activity-related energy expenditure using accelerometer-derived physical activity under free-living conditions: a systematic review
Jeran, S., Steinbrecher, A., & Pischon, T. (2016) · International Journal of Obesity · doi:10.1038/ijo.2016.14 · Cited by 60

Authors: CHEN, K. Y., & BASSETT, D. R.
Affiliations: Vanderbilt University (US)
University of Tennessee at Knoxville (US)
ORCID: CHEN, KONG Y.
BASSETT, DAVID R.
Venue: Medicine & Science in Sports & Exercise
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2005-11
Volume: 37
Issue: 11
Pages: S490-S500
ISSN: 0195-9131 (ISSN-L)
DOI: 10.1249/01.mss.0000185571.49104.82
OpenAlex: W2033727719
Cited by: 996
References: 61
Citations by year: 2026: 15 · 2025: 12 · 2024: 38 · 2023: 20 · 2022: 40 · 2021: 37 · 2020: 51 · 2019: 48 · 2018: 42 · 2017: 65 · 2016: 83 · 2015: 57 · 2014: 84 · 2013: 83 · 2012: 82
FWCI: 14.78
Type: journal article
Language: en
Open access: closed
Locations: Medicine & Science in Sports & Exercise (publishedVersion)
PubMed (publishedVersion)
Funders: National Institute of Diabetes and Digestive and Kidney Diseases (DK 02973, DK 069465, R01DK069465, DK26557, K25DK002973)
National Center for Research Resources (RR00095)
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 › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
Keywords: accelerometry, wearable activity trackers, energy expenditure estimation, multi-sensor array, nonlinear prediction model, physical activity measurement, indirect calorimetry
MeSH terms: Acceleration, Diffusion of Innovation, Equipment Design, Humans, Locomotion, United States, Ergometry

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

The Technology of Accelerometry-Based Activity Monitors: Current and Future

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks