Rowlands, Alex V.

GGIR: A Research Community–Driven Open Source R Package for Generating Physical Activity and Sleep Outcomes from Multi-Day Raw Accelerometer Data

Migueles, J. H., Rowlands, A. V., Huber, F., Sabia, S., & van Hees, V. T. (2019) · Journal for the Measurement of Physical Behaviour

Physical Activity and HealthContext-Aware Activity Recognition Systems

Cited by 955

The validity of consumer-level, activity monitors in healthy adults worn in free-living conditions: a cross-sectional study

Ferguson, T., Rowlands, A. V., Olds, T., & Maher, C. (2015) · International Journal of Behavioral Nutrition and Physical Activity

Physical Activity and HealthContext-Aware Activity Recognition Systems

Cited by 468

Physical activity, multimorbidity, and life expectancy: a UK Biobank longitudinal study

Chudasama, Y. V., Khunti, K. K., Zaccardi, F., Rowlands, A. V., Yates, T., Gillies, C. L., Davies, M. J., & Dhalwani, N. N. (2019) · BMC Medicine

Physical Activity and HealthChronic Disease Management Strategies

Cited by 353

Physical Activity Classification Using the GENEA Wrist-Worn Accelerometer

ZHANG, S., ROWLANDS, A. V., MURRAY, P., & HURST, T. L. (2012) · Medicine & Science in Sports & Exercise

Context-Aware Activity Recognition SystemsPhysical Activity and Health

Cited by 233

Accelerometer-assessed Physical Activity in Epidemiology: Are Monitors Equivalent?

ROWLANDS, A. V., MIRKES, E. M., YATES, T., CLEMES, S., DAVIES, M., KHUNTI, K., & EDWARDSON, C. L. (2018) · Medicine & Science in Sports & Exercise

Physical Activity and HealthContext-Aware Activity Recognition Systems

Cited by 187

Short-term and Long-term Feasibility, Safety, and Efficacy of High-Intensity Interval Training in Cardiac Rehabilitation: The FITR Heart Study Randomized Clinical Trial

Taylor, J. L., Holland, D. J., Keating, S. E., Leveritt, M. D., Gomersall, S. R., Rowlands, A. V., Bailey, T. G., & Coombes, J. S. (2020) · JAMA Cardiology

Cardiovascular and exercise physiologyCardiac Health and Mental Health

Cited by 148

Comparability and feasibility of wrist- and hip-worn accelerometers in free-living adolescents.

Scott, J. J., Rowlands, A. V., Cliff, D. P., Morgan, P. J., Plotnikoff, R. C., & Lubans, D. R. (2017) · Journal of Science and Medicine in Sport

Physical Activity and HealthContext-Aware Activity Recognition Systems

Cited by 120

Prediction of DXA-Determined Whole Body Fat from Skinfolds: Importance of Including Skinfolds from the Thigh and Calf in Young, Healthy Men and Women

Eston, R. G., Rowlands, A. V., Charlesworth, S., Davies, A., & Hoppitt, T. (2005) · European Journal of Clinical Nutrition

Body Composition Measurement TechniquesObesity, Physical Activity, Diet

Cited by 89

Moving forward with accelerometer-assessed physical activity: two strategies to ensure meaningful, interpretable, and comparable measures

Rowlands, A. V. (2018) · Pediatric Exercise Science

Physical Activity and HealthContext-Aware Activity Recognition Systems

Cited by 87

Metabolic Effects of Breaking Prolonged Sitting With Standing or Light Walking in Older South Asians and White Europeans: A Randomized Acute Study

Yates, T., Edwardson, C. L., Celis-Morales, C., Biddle, S. J. H., Bodicoat, D., Davies, M. J., Esliger, D., Henson, J., Kazi, A., Khunti, K., et al. (2020) · The Journals of Gerontology: Series A

Physical Activity and HealthDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 87

Wrist-worn accelerometers: recommending ~1.0 m g as the minimum clinically important difference (MCID) in daily average acceleration for inactive adults

Rowlands, A., Davies, M., Dempsey, P., Edwardson, C., Razieh, C., & Yates, T. (2021) · British Journal of Sports Medicine

Physical Activity and HealthContext-Aware Activity Recognition Systems

Cited by 74

Waking Up to the Importance of Sleep in Type 2 Diabetes Management: A Narrative Review.

Henson, J., Covenant, A., Hall, A. P., Herring, L., Rowlands, A. V., Yates, T., & Davies, M. J. (2024) · Diabetes Care

Sleep and related disordersCircadian rhythm and melatonin

Cited by 69

Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality

Yuan, H., Plekhanova, T., Walmsley, R., Reynolds, A. C., Maddison, K. J., Bucan, M., Gehrman, P., Rowlands, A., Ray, D. W., Bennett, D., et al. (2024) · npj Digital Medicine

Sleep and related disordersContext-Aware Activity Recognition Systems

Cited by 40

Stepping towards More Intuitive Physical Activity Metrics with Wrist-Worn Accelerometry: Validity of an Open-Source Step-Count Algorithm

Maylor, B. D., Edwardson, C. L., Dempsey, P. C., Patterson, M. R., Plekhanova, T., Yates, T., & Rowlands, A. V. (2022) · Sensors

Physical Activity and HealthContext-Aware Activity Recognition Systems

Cited by 30

Absolute intensity thresholds for tri‐axial wrist and waist accelerometer‐measured movement behaviors in adults

Mielke, G. I., de Almeida Mendes, M., Ekelund, U., Rowlands, A. V., Reichert, F. F., & Crochemore‐Silva, I. (2023) · Scandinavian Journal of Medicine & Science in Sports

Physical Activity and HealthContext-Aware Activity Recognition Systems

Cited by 26

Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance

Migueles, J. H., Molina-Garcia, P., Torres-Lopez, L. V., Cadenas-Sanchez, C., Rowlands, A. V., Ebner-Priemer, U. W., Koch, E. D., Reif, A., & Ortega, F. B. (2022) · Scientific Reports

Physical Activity and HealthContext-Aware Activity Recognition Systems

Cited by 22

Greater hepatic lipid saturation is associated with impaired glycaemic regulation in men with metabolic dysfunction‐associated steatotic liver disease but is not altered by 6 weeks of exercise training

Willis, S. A., Malaikah, S., Bawden, S. J., Sherry, A. P., Sargeant, J. A., Coull, N. A., Bradley, C. R., Rowlands, A., Naim, I., Ennequin, G., et al. (2024) · Diabetes, Obesity and Metabolism

Liver Disease Diagnosis and TreatmentDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 9

Associations between objectively assessed and questionnaire-based sedentary behaviour with body mass index and systolic blood pressure in Kuwaiti adolescents

Hashem, R., Rey-Lόpez, J. P., Hamer, M., McMunn, A., Rowlands, A., Whincup, P. H., Owen, C. G., Ding, D., Powell, L., & Stamatakis, E. (2019) · BMC Research Notes

Physical Activity and HealthObesity, Physical Activity, Diet

Cited by 8

Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality

Yuan, H., Plekhanova, T., Walmsley, R., Reynolds, A. C., Maddison, K. J., Bucan, M., Gehrman, P., Rowlands, A., Ray, D. W., Bennett, D., et al. (2023) · medRxiv

Sleep and related disordersContext-Aware Activity Recognition Systems

Cited by 3

Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality

Doherty, A., Yuan, H., Plekhanova, T., Walmsley, R., Reynolds, A., Maddison, K., Bucan, M., Gehrman, P., Rowlands, A., Ray, D., et al. (2023) · Research Square

Sleep and related disordersContext-Aware Activity Recognition Systems

Cited by 0