222 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]