This research presents a novel method for objectively assessing infants' motor abilities using a multi-sensor wearable, MAIJU. The study involved 59 infants aged 5-19 months, recorded during spontaneous play. A deep learning-based classifier, trained on a novel gross motor description scheme, achieved human-equivalent accuracy in quantifying postures and movements. Aggregated data were used to create the Baba Infant Motor Score (BIMS), strongly correlating with chronological age (r = 0.89, p < 1e-20). This wearable technology enables out-of-hospital assessment, offering a scalable and objective solution for early neurodevelopmental care.
Publisher
Communications Medicine
Published On
Jun 15, 2022
Authors
Manu Airaksinen, Anastasia Gallen, Anna Kivi, Pavithra Vijayakrishnan, Taru Häyrinen, Elina Ilén, Okko Räsänen, Leena M. Haataja, Sampsa Vanhatalo
Tags
infants
motor abilities
multi-sensor wearable
deep learning
neurodevelopment
objective assessment
Baba Infant Motor Score
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