# An Automated Early Motor Development Risk Screener from Observational Video Recordings of Infants and Toddlers

> **NIH NIH R44** · BSOLUTIONS, INC. · 2020 · $601,447

## Abstract

Motor development plays a pivotal role in an infant’s overall development and has a cascading effect on social,
cognitive, memory, and language ability. These functions can be compromised when motor development is
disrupted; motor disruption is associated with generalized developmental delays. Early screening and
identification of delays can allow early interventions with the goal of not just improving motor function but overall
development in other domains. Experience with independent or motorized crawling is shown to improve spatial
memory in infants. Active motor training, even as early as 3 months, is shown to achieve gains in object
exploration and social engagement that persist long after the training sessions, indicating the benefits of early
intervention.
Children who get developmental screening are more likely to be identified with delays and receive early
intervention services compared to those that only receive age-appropriate milestone checks as part of pediatric
well-child visits. However, comprehensive motor screening, using standardized instruments, for developmental
surveillance is labor intensive and requires specialized training in administration and evaluation. Shortage of
resources to perform frequent, gold-standard, comprehensive motor assessments can lead to missed
opportunities for early intervention and contribute negatively to lifelong outcomes for infants at risk for behavioral
and developmental disorders. In the US, 15-20% of children have a developmental or behavioral disability, but
less than a third of them get diagnosed before entering school, preventing opportunities for early intervention
during a critical period of brain development.
In Phase I, we built a prototype Human Action Recognition Engine (HARE) to automate extraction of infant motor
movement from video; then utilized this engine to demonstrate the feasibility of an automated developmental
risk screener by leveraging recent advances in machine learning to achieve state of the art accuracies in
assessment of infant motor development. In Phase II, we aim to build out the risk screener, SCOREIT, as a
clinically deployable, cost-effective, developmental risk assessment tool to identify children who need further
clinical follow-up. SCOREIT has the potential to transform early developmental screening by bringing the power
of comprehensive motor screening, usually administered only to at-risk children utilizing specialized resources,
to underserved and economically-fragile communities. Less than a third of US children receive developmental
screening. SCOREIT can bring risk screenings to the over 70% of children that currently do not receive them,
increasing opportunities for early intervention for behavioral and developmental disorders. Additionally, the
HARE system’s ability to automatically extract and quantify motor movements from video can be an enabler for
explorations of early markers for behavioral and developmental disorders, significantly easing manual...

## Key facts

- **NIH application ID:** 9785611
- **Project number:** 5R44HD095783-04
- **Recipient organization:** BSOLUTIONS, INC.
- **Principal Investigator:** BHARATH MODAYUR
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $601,447
- **Award type:** 5
- **Project period:** 2018-03-01 → 2021-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9785611

## Citation

> US National Institutes of Health, RePORTER application 9785611, An Automated Early Motor Development Risk Screener from Observational Video Recordings of Infants and Toddlers (5R44HD095783-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9785611. Licensed CC0.

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