0000000000794408

AUTHOR

Michael J. Duncan

0000-0002-2016-6580

showing 2 related works from this author

Profiling movement behaviours in pre-school children: A self-organised map approach.

2019

Application of machine learning techniques has the potential to yield unseen insights into movement and permits visualisation of complex behaviours and tangible profiles. The aim of this study was to identify profiles of relative motor competence (MC) and movement behaviours in pre-school children using novel analytics. One-hundred and twenty-five children (4.3 ± 0.5y, 1.04 ± 0.05 m, 17.8 ± 3.2 kg, BMI: 16.2 ± 1.9 kg

MaleComputer scienceMovementPhysical activity030209 endocrinology & metabolismPhysical Therapy Sports Therapy and Rehabilitation030229 sport sciencesFitness TrackersMotor ActivityVisualizationBody Mass IndexMachine Learning03 medical and health sciences0302 clinical medicineCross-Sectional StudiesHuman–computer interactionChild PreschoolAccelerometryProfiling (information science)HumansOrthopedics and Sports MedicinePre schoolFemaleExerciseJournal of sports sciences
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O8-1 24-Hour Movement Behavior and Fundamental Movement Skills in Pre-School Children: A Compositional Analysis

2022

Abstract Background Studies that have analyzed the association between the different movement behaviors and fundamental movement skills (FMS), have considered it in an independent manner, disregarding the compositional nature of 24-hour movement behaviors (24h MB). The aim of this study was to investigate relationships between the 24h MB and FMS in low-income preschoolers. Methods Two hundred and four preschoolers of both sexes (4.5±0.8 years old; 101boys) provided objectively assessed physical activity (PA) and sedentary time (ST) data (Actigraph wGT3X), and FMS assessments (TGMD-2). Sleep duration (SD) was reported by parents through interview. Association of daily time composition of mov…

Public Health Environmental and Occupational HealthEuropean Journal of Public Health
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