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Physical activity in children and adolescents with CHD: review from a measurement methodological perspective

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Concurrent Validity of Different Sensor-Based Measures: Activity Counts Do Not Reflect Functional Hand Use in Children and Adolescents With Upper Limb Impairments

Rast, F. M., & Labruyère, R. (2022) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2022.03.021 · Cited by 10

Children and Adolescents Treated for Valvular Aortic Stenosis Have Different Physical Activity Patterns Compared to Healthy Controls: A Methodological Study in a National Cohort

Skovdahl, P., Olofsson, C. K., Sunnegårdh, J. T., Fridolfsson, J., Börjesson, M., Buratti, S., & Arvidsson, D. (2021) · Pediatric Cardiology · doi:10.1007/s00246-021-02540-1 · Cited by 9

Comprehensive evaluation of accelerometer-based physical activity in persons with multiple sclerosis – The influence of disability status and its impact on walking capacity

Andersen, T. M., Andersen, A. M., Riemenschneider, M., Taul-Madsen, L., Diechmann, M., Gaemelke, T., Dalgas, U., Brønd, J. C., & Hvid, L. G. (2024) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2024.106243 · Cited by 8

Effects of a Wearable-Based Intervention on the Hemiparetic Upper Limb in Persons With Stroke: A Randomized Controlled Trial

Toh, S. F. M., Lam, W. W. T., González, P. C., & Fong, K. N. K. (2024) · Neurorehabilitation and neural repair · doi:10.1177/15459683241283412 · Cited by 9

Changes in physical activity by context and residential greenness among recent retirees: Longitudinal GPS and accelerometer study

Pasanen, S., Halonen, J. I., Gonzales‐Inca, C., Pentti, J., Vahtera, J., Kestens, Y., Thierry, B., Brondeel, R., Leskinen, T., & Stenholm, S. (2021) · Health & Place · doi:10.1016/j.healthplace.2021.102732 · Cited by 7

Measuring Foot Abduction Brace Wear Time Using a Single 3-Axis Accelerometer

Griffiths, B., Silver, N., Granat, M. H., & Lebel, E. (2022) · Sensors · doi:10.3390/s22072433 · Cited by 7

Does work-related and commuting physical activity predict changes in physical activity and sedentary behavior during the transition to retirement? GPS and accelerometer study

Pasanen, S., Halonen, J. I., Suorsa, K., Leskinen, T., Kestens, Y., Thierry, B., Pentti, J., Vahtera, J., & Stenholm, S. (2023) · Health & Place · doi:10.1016/j.healthplace.2023.103025 · Cited by 8

Development and Validation of Open-Source Activity Intensity Count and Activity Intensity Classification Algorithms from Raw Acceleration Signals of Wearable Sensors

Poitras, I., Clouâtre, J., Bouyer, L. J., Routhier, F., Mercier, C., & Campeau‐Lecours, A. (2020) · Sensors · doi:10.3390/s20236767 · Cited by 7

Challenges and opportunities related to the objective assessment of physical activity within U.S. health surveys

LaMunion, S. R., Fitzhugh, E. C., & Crouter, S. E. (2020) · Annals of Epidemiology · doi:10.1016/j.annepidem.2020.01.011 · Cited by 7

Using combined Global Position System and accelerometer data points to examine how built environments and gentrification are associated with physical activity in four Canadian cities

Firth, C. L., Kestens, Y., Winters, M., Stanley, K. G., Bell, S., Thierry, B., Phillips, K., Stephens, Z. P., & Fuller, D. (2022) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-022-01306-z · Cited by 7

Energy Expenditure Prediction from Accelerometry Data Using Long Short-Term Memory Recurrent Neural Networks

Vibæk, M., Peimankar, A., Wiil, U. K., Arvidsson, D., & Brønd, J. C. (2024) · Sensors · doi:10.3390/s24082520 · Cited by 9

Comparison of two tri-axial accelerometers for measuring locomotor activity in ewes and lambs

Abecia, J. A., Aguerri, C., & Canto, F. (2024) · Smart Agricultural Technology · doi:10.1016/j.atech.2024.100496 · Cited by 6

Physical activity estimation from accelerometry

Garnotel, M., Simon, C., & Bonnet, S. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8856957 · Cited by 6

Human Activity Classification Based on Angle Variance Analysis Utilizing the Poincare Plot

Ahmed, S., Bhuiyan, T. A., Kishi, T., Nii, M., & Kobashi, S. (2021) · Applied Sciences · doi:10.3390/app11167230 · Cited by 6

Establishing Accelerometer Cut-Points to Classify Walking Speed in People Post Stroke

Conradsson, D. M., & Bezuidenhout, L. (2022) · Sensors · doi:10.3390/s22114080 · Cited by 6

Online Physical Exercise and Group Sessions to Increase and Maintain Physical Activity in Individuals with Type 2 Diabetes: A Single-Arm Feasibility Study

Mortensen, S. R., Pedersen, M. E., Skou, S. T., & Ried‐Larsen, M. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20042893 · Cited by 6

Influence of Accelerometer Calibration on the Estimation of Objectively Measured Physical Activity: The Tromsø Study

Weitz, M., Morseth, B., Hopstock, L. A., & Horsch, A. (2024) · Journal for the Measurement of Physical Behaviour · doi:10.1123/jmpb.2023-0019 · Cited by 6

Quantification of Acceleration as Activity Counts in ActiGraph WearablesPreprint

Neishabouri, A., Nguyen, J., Samuelsson, J. G., Guthrie, T., Biggs, M., Wyatt, J. C., Cross, D., Karas, M., Migueles, J. H., Khan, S., et al. (2022) · Research Square · doi:10.21203/rs.3.rs-1370418/v1 · Cited by 6

Validation of physical activity levels from shank-placed Axivity AX6 accelerometers in older adults

Gafoor, F., Ruder, M. C., & Kobsar, D. (2024) · PLoS ONE · doi:10.1371/journal.pone.0290912 · Cited by 5

Introducing an adjustable upper limb prosthesis into a Ugandan clinical service: impacts on free living behaviour and prosthetic use

Pickard, N., Mulindwa, B., Gracey-McMinn, L., Granat, M. H., Chadwell, A., Curtin, S., Howard, D., Ackers, L., Ssekitoleko, R., & Kenney, L. P. J. (2025) · Scientific Reports · doi:10.1038/s41598-025-96779-w · Cited by 5

On the Unification of Common Actigraphic Data Scoring Algorithms

Biegański, P., Stróż, A., Dovgialo, M., Duszyk-Bogorodzka, A., & Durka, P. J. (2021) · Sensors · doi:10.3390/s21186313 · Cited by 5

Count‐ versus MAD‐based accelerometry‐assessed movement behaviors and associations with child adiposity and fitness

Verswijveren, S. J. J. M., Douglas, B., Rantalainen, T., Belavý, D. L., Salmon, J., Timperio, A. F., Lubans, D. R., & Ridgers, N. D. (2021) · Scandinavian Journal of Medicine and Science in Sports · doi:10.1111/sms.14051 · Cited by 5

The Validity of the Energy Expenditure Criteria Based on Open Source Code through two Inertial Sensors

Martín‐Martín, J., Wang, L., De-Torres, I., Escriche-Escuder, A., González‐Sánchez, M., Muro-Culebras, A., Roldán‐Jiménez, C., Ruiz‐Muñoz, M., Mayoral, F., Biró, A., et al. (2022) · Sensors · doi:10.3390/s22072552 · Cited by 6

Predicting lying, sitting and walking at different intensities using smartphone accelerometers at three different wear locations: hands, pant pockets, backpack

Khataeipour, S. J., Anaraki, J. R., Bozorgi, A., Rayner, M., Basset, F. A., & Fuller, D. (2022) · BMJ Open Sport & Exercise Medicine · doi:10.1136/bmjsem-2021-001242 · Cited by 5

Does accelerometry reflect hand function in infants at risk of unilateral cerebral palsy? A secondary analysis of BB-Bim results

Bard-Pondarré, R., Abiad, N. A., Verdun, S., Naaïm, A., Agopyan, H., Chaléat-Valayer, E., & Vuillerot, C. (2023) · Research in Developmental Disabilities · doi:10.1016/j.ridd.2023.104549 · Cited by 5

Cross-Validation and Comparison of Energy Expenditure Prediction Models Using Count-Based and Raw Accelerometer Data in Youth

Montoye, A. H. K., Clevenger, K. A., Mackintosh, K. A., McNarry, M. A., & Pfeiffer, K. A. (2019) · Journal for the Measurement of Physical Behaviour · doi:10.1123/jmpb.2018-0011 · Cited by 5

Comparison of Wearable Sensor Based Algorithms for Upper Limb Activity Detection

Subash, T., David, A., Varadhan, S. K. M., & Balasubramanian, S. (2021) · Biosystems & biorobotics · doi:10.1007/978-3-030-70316-5_72 · Cited by 5

The lifestyle of new middle-aged and older adults in Taiwan described by wearable device: age and gender differences

Wang, C.-L., Li, C.-X., & Liang, S. (2024) · European Journal of Ageing · doi:10.1007/s10433-024-00824-y · Cited by 4

Associations between number and type of conditions and physical activity levels in adults with multimorbidity - a cross-sectional study from the Danish Lolland-Falster health study

Jørgensen, L. B., Mortensen, S. R., Tang, L. H., Grøntved, A., Brønd, J. C., Jepsen, R., Petersen, T. L., & Skou, S. T. (2024) · Journal of Multimorbidity and Comorbidity · doi:10.1177/26335565241307614 · Cited by 4

From Raw Acceleration Data to Activity Count

Rao, Z., & Albinali, F. (2016) · Medicine & Science in Sports & Exercise · doi:10.1249/01.mss.0000487359.02777.91 · Cited by 1

Exploring the ActiLife®filtration algorithm: converting raw acceleration data to counts

Peach, D., Hoomissen, J. V., & Callender, H. L. (2014) · Physiological Measurement · doi:10.1088/0967-3334/35/12/2359 · Cited by 30

Shaking Up Activity Counts: Assessing the Comparability of Accelerometers and Activity Count Computation

Coyle-Asbil, H. J., Murphy, B. A., & Vallis, L. A. (2024) · Journal for the Measurement of Physical Behaviour · doi:10.1123/jmpb.2023-0058 · Cited by 2

A Walkthrough of ActiGraph Counts

Neishabouri, A., Nguyen, J., Patterson, M., Pilkar, R. B., & Guo, C. C. (2024) · Journal for the Measurement of Physical Behaviour · doi:10.1123/jmpb.2023-0048 · Cited by 3

Sampling frequency affects the processing of Actigraph raw acceleration data to activity counts

Brønd, J. C., & Arvidsson, D. (2015) · Journal of Applied Physiology · doi:10.1152/japplphysiol.00628.2015 · Cited by 148