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