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

Charlotte Lund Rasmussen, Danica Hendry, George Thomas, Amber Beynon, Sarah Michelle Stearne, Juliana Zabatiero, Paul Davey, Jon Roslyng Larsen, Andrew Lloyd Rohl, Leon Straker, Amity Campbell

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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.

OriginalsprogEngelsk
TidsskriftSensors
Vol/bind24
Udgave nummer20
ISSN1424-8220
DOI
StatusUdgivet - 18 okt. 2024

Emneord

  • Nye teknologier
  • Software

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