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

6533b833fe1ef96bd129b808

RESEARCH PRODUCT

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

Gareth Stratton Cain C T Clark Michael J. Duncan Xavier García Massó Emma L. J. Eyre Isaac Estevan

subject

Male Computer science Movement Physical activity 030209 endocrinology & metabolism Physical Therapy Sports Therapy and Rehabilitation 030229 sport sciences Fitness Trackers Motor Activity Visualization Body Mass Index Machine Learning 03 medical and health sciences 0302 clinical medicine Cross-Sectional Studies Human–computer interaction Child Preschool Accelerometry Profiling (information science)Humans Orthopedics and Sports Medicine Pre school Female Exercise

description

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

year	journal	country	edition	language
2019-11-07	Journal of sports sciences

10.1080/02640414.2019.1686942 https://pubmed.ncbi.nlm.nih.gov/31699000

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