Medicine and Health

Intelligent wearable allows out-of-the-lab tracking of developing motor abilities in infants

M. Airaksinen, A. Gallen, et al.

This groundbreaking research from Manu Airaksinen and colleagues introduces a multi-sensor wearable, MAIJU, to objectively assess infants' motor abilities during play. By employing a deep learning-based classifier, they created the Baba Infant Motor Score (BIMS), which shows a strong correlation with age, revolutionizing early neurodevelopmental care with scalable, out-of-hospital assessments.

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Abstract

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

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