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Updated: May 24, 2025
Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
Published on: May 17, 2024
Assessing Infant Gross Motor Performance With an At-Home Wearable
Manu Airaksinen1, Anastasia Gallen1, Elisa Taylor1
1BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, New Children's Hospital and HUS Imaging, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
Insights
Wearable sensors accurately track infant gross motor skills development at home. This technology offers reliable, automated quantification for healthcare and developmental studies.
Area of Science:
- Pediatric Development
- Biomedical Engineering
- Motor Control
Background:
- Gross motor skills are crucial for neurocognitive development in infants.
- Current methods for tracking motor development can be resource-intensive.
- Investigating novel, at-home methods for objective motor skill assessment is needed.
Purpose of the Study:
- To evaluate the efficacy of at-home wearable measurements for quantifying infant motor abilities.
- To develop and validate machine learning algorithms for tracking gross motor milestones (GMMs) and motor development.
- To assess the reliability of wearable data compared to established benchmarks.
Main Methods:
- Utilized a multisensor wearable suit for unsupervised, at-home infant activity recordings (n=134, ages 4-22 months).
- Developed machine learning algorithms to detect GMMs, measure postural times, and track longitudinal motor development.
- Validated algorithms using parental questionnaires and benchmarked against World Health Organization (WHO) interrater agreement levels.
Main Results:
- Algorithms demonstrated high accuracy in detecting GMMs (90.9%-96.8%), comparable to human experts.
- Wearable-derived postural times strongly correlated with parental assessments (ρ = .48-.81).
- Individual motor maturation trajectories showed a strong correlation with infant age (ρ = .93).
Conclusions:
- Infants' gross motor skills can be reliably and automatically quantified using unsupervised, at-home wearable recordings.
- This methodology provides objective, real-world data for tracking motor abilities.
- Potential applications include healthcare practice and developmental research.
Background:
Early development of gross motor skills is foundational for the upcoming neurocognitive performance. Here, we studied whether at-home wearable measurements performed by the parents could be used to quantify and track infants' developing motor abilities.
Methods:
Unsupervised at-home measurements of the infants' spontaneous activity were made repeatedly by the parents using a multisensor wearable suit (altogether 620 measurements from 134 infants at age 4-22 months). Machine learning-based algorithms were developed to detect the reaching of gross motor milestones (GMM), to measure times spent in key postures, and to track the overall motor development longitudinally. Parental questionnaires regarding GMMs were used for developing the algorithms, and the results were benchmarked with the interrater agreement levels established by World Health Organization (WHO). A total of 97 infants were used for the algorithm development and cross-validation, whereas an external validation was done using 37 infants from an independent recruitment in the same hospital.
Results:
The algorithms detected the reaching of GMMs very accurately (cross-validation: accuracy, 90.9%-95.5%; external validation, 92.4%-96.8%), which compares well with the human experts in the WHO reference study. The wearable-derived postural times showed strong correlation to parental assessments (ρ = .48-.81). Individual trajectories of motor maturation showed strong correlation to infants' age (ρ = .93).
Conclusions:
These findings suggest that infants' gross motor skills can be quantified reliably and automatically from unsupervised at-home wearable recordings. Such methodology could be used in health care practice and in all developmental studies for gaining real-world quantitation and tracking of infants' motor abilities.
