Evaluation of the ActiMotus Software to Accurately Classify Postures and Movements in Children Aged 3-14

Sensors (Basel). 2024 Oct 18;24(20):6705. doi: 10.3390/s24206705.

Abstract

Background: ActiMotus, a thigh-accelerometer-based software used for the classification of postures and movements (PaMs), has shown high accuracy among adults and school-aged children; however, its accuracy among younger children and potential differences between sexes are unknown. This study aimed to evaluate the accuracy of ActiMotus to measure PaMs among children between 3 and 14 years and to assess if this was influenced by the sex or age of children.

Method: Forty-eight children attended a structured ~1-hour data collection session at a laboratory. Thigh acceleration was measured using a SENS accelerometer, which was classified into nine PaMs using the ActiMotus software. Human-coded video recordings of the session provided the ground truth.

Results: Based on both F1 scores and balanced accuracy, the highest levels of accuracy were found for lying, sitting, and standing (63.2-88.2%). For walking and running, accuracy measures ranged from 48.0 to 85.8%. The lowest accuracy was observed for classifying stair climbing. We found a higher accuracy for stair climbing among girls compared to boys and for older compared to younger age groups for walking, running, and stair climbing.

Conclusions: ActiMotus could accurately detect lying, sitting, and standing among children. The software could be improved for classifying walking, running, and stair climbing, particularly among younger children.

Keywords: accelerometry; physical activity; sedentary behaviour; validation.

MeSH terms

  • Accelerometry* / methods
  • Adolescent
  • Child
  • Child, Preschool
  • Female
  • Humans
  • Male
  • Movement* / physiology
  • Posture* / physiology
  • Running / physiology
  • Software*
  • Walking / physiology