These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
217 related articles for article (PubMed ID: 30936837)
1. Estimating Physical Activity in Children Aged 8-11 Years Using Accelerometry: Contributions From Fundamental Movement Skills and Different Accelerometer Placements. Duncan MJ; Roscoe CMP; Faghy M; Tallis J; Eyre ELJ Front Physiol; 2019; 10():242. PubMed ID: 30936837 [TBL] [Abstract][Full Text] [Related]
2. Calibration and Cross-Validation of Accelerometery for Estimating Movement Skills in Children Aged 8-12 Years. Duncan MJ; Dobell A; Noon M; Clark CCT; Roscoe CMP; Faghy MA; Stodden D; Sacko R; Eyre ELJ Sensors (Basel); 2020 May; 20(10):. PubMed ID: 32414192 [TBL] [Abstract][Full Text] [Related]
3. Predicting children's energy expenditure during physical activity using deep learning and wearable sensor data. Hamid A; Duncan MJ; Eyre ELJ; Jing Y Eur J Sport Sci; 2021 Jun; 21(6):918-926. PubMed ID: 32597337 [TBL] [Abstract][Full Text] [Related]
4. Using accelerometry to classify physical activity intensity in older adults: What is the optimal wear-site? Duncan MJ; Rowlands A; Lawson C; Leddington Wright S; Hill M; Morris M; Eyre E; Tallis J Eur J Sport Sci; 2020 Sep; 20(8):1131-1139. PubMed ID: 31726952 [No Abstract] [Full Text] [Related]
5. Validation of the Phillips et al. GENEActiv accelerometer wrist cut-points in children aged 5-8 years old. Duncan MJ; Wilson S; Tallis J; Eyre E Eur J Pediatr; 2016 Dec; 175(12):2019-2021. PubMed ID: 27785561 [TBL] [Abstract][Full Text] [Related]
6. Calibration of GENEActiv accelerometer wrist cut-points for the assessment of physical activity intensity of preschool aged children. Roscoe CMP; James RS; Duncan MJ Eur J Pediatr; 2017 Aug; 176(8):1093-1098. PubMed ID: 28674825 [TBL] [Abstract][Full Text] [Related]
7. Comparison of Indirect Calorimetry- and Accelerometry-Based Energy Expenditure During Children's Discrete Skill Performance. Sacko R; McIver K; Brazendale K; Pfeifer C; Brian A; Nesbitt D; Stodden DF Res Q Exerc Sport; 2019 Dec; 90(4):629-640. PubMed ID: 31441713 [No Abstract] [Full Text] [Related]
8. Cross-validation of Actigraph derived accelerometer cut-points for assessment of sedentary behaviour and physical activity in children aged 8-11 years. Duncan MJ; Eyre ELJ; Cox V; Roscoe CMP; Faghy MA; Tallis J; Dobell A Acta Paediatr; 2020 Sep; 109(9):1825-1830. PubMed ID: 31984545 [TBL] [Abstract][Full Text] [Related]
9. Wrist-worn triaxial accelerometry predicts the energy expenditure of non-vigorous daily physical activities. Sirichana W; Dolezal BA; Neufeld EV; Wang X; Cooper CB J Sci Med Sport; 2017 Aug; 20(8):761-765. PubMed ID: 28159535 [TBL] [Abstract][Full Text] [Related]
10. Calibration of the GENEA accelerometer for assessment of physical activity intensity in children. Phillips LR; Parfitt G; Rowlands AV J Sci Med Sport; 2013 Mar; 16(2):124-8. PubMed ID: 22770768 [TBL] [Abstract][Full Text] [Related]
11. A random forest classifier for the prediction of energy expenditure and type of physical activity from wrist and hip accelerometers. Ellis K; Kerr J; Godbole S; Lanckriet G; Wing D; Marshall S Physiol Meas; 2014 Nov; 35(11):2191-203. PubMed ID: 25340969 [TBL] [Abstract][Full Text] [Related]
12. Evaluation of Wrist Accelerometer Cut-Points for Classifying Physical Activity Intensity in Youth. Trost SG; Brookes DSK; Ahmadi MN Front Digit Health; 2022; 4():884307. PubMed ID: 35585912 [TBL] [Abstract][Full Text] [Related]
13. Separating bedtime rest from activity using waist or wrist-worn accelerometers in youth. Tracy DJ; Xu Z; Choi L; Acra S; Chen KY; Buchowski MS PLoS One; 2014; 9(4):e92512. PubMed ID: 24727999 [TBL] [Abstract][Full Text] [Related]
14. Normative wrist-worn accelerometer values for self-paced walking and running: a walk in the park. Dawkins NP; Yates T; Soczawa-Stronczyk AA; Bocian M; Edwardson CL; Maylor B; Davies MJ; Khunti K; Rowlands AV J Sports Sci; 2022 Jan; 40(1):81-88. PubMed ID: 34544319 [TBL] [Abstract][Full Text] [Related]
15. Calibration and Cross-Validation of Accelerometer Cut-Points to Classify Sedentary Time and Physical Activity from Hip and Non-Dominant and Dominant Wrists in Older Adults. Migueles JH; Cadenas-Sanchez C; Alcantara JMA; Leal-Martín J; Mañas A; Ara I; Glynn NW; Shiroma EJ Sensors (Basel); 2021 May; 21(10):. PubMed ID: 34064790 [TBL] [Abstract][Full Text] [Related]
16. Wrist Accelerometer Estimates of Physical Activity Intensity During Walking in Older Adults and People Living With Complex Health Conditions: Retrospective Observational Data Analysis Study. Weber KS; Godkin FE; Cornish BF; McIlroy WE; Van Ooteghem K JMIR Form Res; 2023 Mar; 7():e41685. PubMed ID: 36920452 [TBL] [Abstract][Full Text] [Related]
17. Personalised Accelerometer Cut-point Prediction for Older Adults' Movement Behaviours using a Machine Learning approach. Nnamoko N; Cabrera-Diego LA; Campbell D; Sanders G; Fairclough SJ; Korkontzelos I Comput Methods Programs Biomed; 2021 Sep; 208():106165. PubMed ID: 34118492 [TBL] [Abstract][Full Text] [Related]
18. Absolute intensity thresholds for tri-axial wrist and waist accelerometer-measured movement behaviors in adults. Mielke GI; de Almeida Mendes M; Ekelund U; Rowlands AV; Reichert FF; Crochemore-Silva I Scand J Med Sci Sports; 2023 Sep; 33(9):1752-1764. PubMed ID: 37306308 [TBL] [Abstract][Full Text] [Related]
19. Validation of the Vivago Wrist-Worn accelerometer in the assessment of physical activity. Vanhelst J; Hurdiel R; Mikulovic J; Bui-Xuân G; Fardy P; Theunynck D; Béghin L BMC Public Health; 2012 Aug; 12():690. PubMed ID: 22913286 [TBL] [Abstract][Full Text] [Related]
20. Physical activity assessment by accelerometry in people with heart failure. Dibben GO; Gandhi MM; Taylor RS; Dalal HM; Metcalf B; Doherty P; Tang LH; Kelson M; Hillsdon M BMC Sports Sci Med Rehabil; 2020; 12():47. PubMed ID: 32817798 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]