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Updated: Jul 31, 2025
Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
Published on: May 17, 2024
Charting infants' motor development at home using a wearable system: validation and comparison to physical growth
Manu Airaksinen1, Elisa Taylor1, Anastasia Gallen1
1BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, New Children's Hospital and HUS Imaging, Helsinki University Hospital, Helsinki, Finland.
Insights
A wearable system accurately assesses infant motor development using automated analysis, comparable to physical growth metrics. This quantitative motor assessment aids diagnostics and early intervention research.
Area of Science:
- Pediatric neurodevelopment
- Wearable technology in infant assessment
- Quantitative motor development analysis
Background:
- Need for practical, quantitative methods in early neurodevelopmental care and research.
- Validation of a wearable system for early motor assessment against physical growth charts.
Purpose of the Study:
- To validate a wearable system for quantitative assessment of early motor development in infants.
- To compare motor development assessment with physical growth tracking.
Main Methods:
- Analysis of 1358 hours of infant movement using a multisensor wearable system and a deep learning pipeline.
- Quantification of infant postures and movements, with comparison between archived and validation cohorts.
- Developmental Age Prediction (DAP) scores derived from motor and physical growth data.
Main Results:
- Age-specific motor patterns were consistent across infant cohorts.
- Developmental Age Prediction scores from motor data showed high correlation with age (97-99% variance explained at group level).
- Motor assessment accuracy (1.4 months variation) was comparable to length (1.5 months) and superior to weight (1.9 months) and head circumference (1.9 months).
Conclusions:
- Fully automated analysis of infant motor performance using wearable systems is feasible and reproducible.
- Holistic motor development assessment offers accuracy comparable to conventional physical growth measures.
- Quantitative motor development measures can support individual diagnostics, care, and serve as outcome measures in early intervention trials.
Background:
Early neurodevelopmental care and research are in urgent need of practical methods for quantitative assessment of early motor development. Here, performance of a wearable system in early motor assessment was validated and compared to developmental tracking of physical growth charts.
Methods:
Altogether 1358 h of spontaneous movement during 226 recording sessions in 116 infants (age 4-19 months) were analysed using a multisensor wearable system. A deep learning-based automatic pipeline quantified categories of infants' postures and movements at a time scale of seconds. Results from an archived cohort (dataset 1, N = 55 infants) recorded under partial supervision were compared to a validation cohort (dataset 2, N = 61) recorded at infants' homes by the parents. Aggregated recording-level measures including developmental age prediction (DAP) were used for comparison between cohorts. The motor growth was also compared with respective DAP estimates based on physical growth data (length, weight, and head circumference) obtained from a large cohort (N = 17,838 infants; age 4-18 months).
Findings:
Age-specific distributions of posture and movement categories were highly similar between infant cohorts. The DAP scores correlated tightly with age, explaining 97-99% (94-99% CI 95) of the variance at the group average level, and 80-82% (72-88%) of the variance in the individual recordings. Both the average motor and the physical growth measures showed a very strong fit to their respective developmental models (R2 = 0.99). However, single measurements showed more modality-dependent variation that was lowest for motor (σ = 1.4 [1.3-1.5 CI 95] months), length (σ = 1.5 months), and combined physical (σ = 1.5 months) measurements, and it was clearly higher for the weight (σ = 1.9 months) and head circumference (σ = 1.9 months) measurements. Longitudinal tracking showed clear individual trajectories, and its accuracy was comparable between motor and physical measures with longer measurement intervals.
Interpretation:
A quantified, transparent and explainable assessment of infants' motor performance is possible with a fully automated analysis pipeline, and the results replicate across independent cohorts from out-of-hospital recordings. A holistic assessment of motor development provides an accuracy that is comparable with the conventional physical growth measures. A quantitative measure of infants' motor development may directly support individual diagnostics and care, as well as facilitate clinical research as an outcome measure in early intervention trials.
Funding:
This work was supported by the Finnish Academy (314602, 335788, 335872, 332017, 343498), Finnish Pediatric Foundation (Lastentautiensäätiö), Aivosäätiö, Sigrid Jusélius Foundation, and HUS Children's Hospital/HUS diagnostic center research funds.
