| Accelerometer measured physical activity and the incidence of cardiovascular disease: Evidence from the UK Biobank cohort study R Ramakrishnan, A Doherty, K Smith-Byrne, K Rahimi, D Bennett, ... PLoS medicine 18 (1), e1003487, 2021 | 165 | 2021 |
| GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in … JH Migueles, E Aadland, LB Andersen, JC Brønd, SF Chastin, BH Hansen, ... British journal of sports medicine 56 (7), 376-384, 2022 | 128 | 2022 |
| Reallocation of time between device-measured movement behaviours and risk of incident cardiovascular disease R Walmsley, S Chan, K Smith-Byrne, R Ramakrishnan, M Woodward, ... British journal of sports medicine 56 (18), 1008-1017, 2022 | 105 | 2022 |
| Compositional associations of sleep and activities within the 24-h cycle with cardiometabolic health markers in adults V Farrahi, M Kangas, R Walmsley, M Niemelä, A Kiviniemi, K Puukka, ... Medicine and science in sports and exercise 53 (2), 324, 2020 | 46 | 2020 |
| Choice architecture modifies fruit and vegetable purchasing in a university campus grocery store: time series modelling of a natural experiment R Walmsley, D Jenkinson, I Saunders, T Howard, O Oyebode BMC Public Health 18, 1-9, 2018 | 38 | 2018 |
| Choice architecture interventions to improve diet and/or dietary behaviour by healthcare staff in high-income countries: a systematic review L Al-Khudairy, OA Uthman, R Walmsley, S Johnson, O Oyebode BMJ open 9 (1), e023687, 2019 | 34 | 2019 |
| Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality H Yuan, T Plekhanova, R Walmsley, AC Reynolds, KJ Maddison, ... NPJ digital medicine 7 (1), 86, 2024 | 18 | 2024 |
| Capture-24: Activity tracker dataset for human activity recognition S Chan Chang, R Walmsley, J Gershuny, T Harms, E Thomas, K Milton, ... University of Oxford, 2021 | 15 | 2021 |
| Your best day: An interactive app to translate how time reallocations within a 24-hour day are associated with health measures D Dumuid, T Olds, M Wake, CL Rasmussen, Ž Pedišić, JH Hughes, ... Plos one 17 (9), e0272343, 2022 | 10 | 2022 |
| Reallocating time from device-measured sleep, sedentary behaviour or light physical activity to moderate-to-vigorous physical activity is associated with lower cardiovascular … R Walmsley, S Chan, K Smith-Byrne, R Ramakrishnan, M Woodward, ... MedRxiv, 2020.11. 10.20227769, 2020 | 10 | 2020 |
| Self-Supervised Machine Learning to Characterize Step Counts from Wrist-Worn Accelerometers in the UK Biobank SR Small, S Chan, R Walmsley, L von Fritsch, A Acquah, G Mertes, ... Medicine and Science in Sports and Exercise 56 (10), 1945, 2024 | 2 | 2024 |
| Amount and intensity of physical activity and risk of incident cancer in the UK Biobank MAH Shreves, SR Small, R Walmsley, S Chan, PF Saint-Maurice, ... medRxiv, 2023 | 1 | 2023 |
| Reproducibility and associated regression dilution bias of accelerometer-derived physical activity and sleep in the UK Biobank C Zisou, H Taylor, B Lacey, I Hammami, R Walmsley, T Strain, ... medRxiv, 2025.01. 16.25320679, 2025 | | 2025 |
| Amount And Intensity Of Daily Physical Activity Measured By Accelerometers And Risk Of Incident Cancer In The Uk Biobank Prospective Cohort: 3059 AH Shreves, SR Small, R Walmsley, S Chan, PF Saint-Maurice, ... Medicine & Science in Sports & Exercise 56 (10S), 1107, 2024 | | 2024 |
| Author Correction: Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality H Yuan, T Plekhanova, R Walmsley, AC Reynolds, KJ Maddison, ... NPJ digital medicine 7 (1), 175, 2024 | | 2024 |
| Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality A Doherty, H Yuan, T Plekhanova, R Walmsley, A Reynolds, K Maddison, ... | | 2023 |
| Device-measured 24-hour movement behaviours and risk of incident cardiovascular disease R Walmsley University of Oxford, 2022 | | 2022 |
| Capture-24: Activity recognition on a large activity tracker dataset collected in the wild S Chan, H Yuan, C Tong, R Walmsley, A Doherty | | |
