# Cribsy: A platform for home-based automated developmental risk screening

> **NIH NIH R43** · BSOLUTIONS, INC. · 2024 · $242,300

## Abstract

In this Phase I application, we introduce Cribsy, an innovative smartphone-based telehealth screener for neuromotor risks
in infants. Our team, with extensive experience in infant motor assessment and robust expertise in machine learning for
video analysis, aims to utilize our vast repository of annotated infant movement data to develop this user-friendly,
automated, at-home screening tool. In the US, 5-10% of children have a developmental disability,1,2,4 but fewer than a
third of them are diagnosed before school entry,3 preventing opportunities for early intervention. The risks of
developmental disorders, including those caused by neuromotor impairments, are particularly high for minorities – Black
(13.3%) and Hispanic (16.7%) infants are twice as likely as their White counterparts (6.5%) to be identified as high-risk
for developmental deficits.5 Research shows that children who are screened for developmental risks 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.9 The American Academy of Pediatrics (AAP) recommends motor
screening to identify at-risk infants at every well-child visit.10,11 Yet, parents skip more than 63% of the recommended 6
well-child visits in the first year.12 Parents in rural and underserved areas have even fewer visits.13 Delaying intervention
until the time of diagnosis may result in missed opportunities to intervene during the period of brain plasticity.22,23 Early
intervention saves up to $100k per child in social service costs.24
Several standardized, norm-referenced tools are available to the clinician for developmental assessments. However, fewer
than 10% of at-risk infants are being screened31 even at highly resourced care centers. The prevalence of at-risk infants far
outstrips the availability of clinicians trained to perform these developmental screening.32 With video conferencing tools
now commonplace post-pandemic, telehealth can expand access to screening for under-served families, but it does not
alleviate the need for trained personnel to execute these screenings synchronously. The innovative solution we are proposing
recruits the parent to acquire the home video data necessary for risk evaluation and employs AI-based methods to automate
video analysis to screen for developmental risks.
In Phase I, the goal is to fully develop Cribsy and transition it from its current limited prototype version to an impactful,
scalable AI system suitable for widespread infant risk screening. This requires attending to product features that promote
adoption as well as streamlining the machine learning processes to address real-world data challenges. Any AI system
encountering real world data runs into the problem of Data Drift, where the statistical properties of the variables the AI
model is trying to predict change in unforeseen ways. The input data properties can change due to dev...

## Key facts

- **NIH application ID:** 10920247
- **Project number:** 1R43HD115478-01
- **Recipient organization:** BSOLUTIONS, INC.
- **Principal Investigator:** BHARATH MODAYUR
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $242,300
- **Award type:** 1
- **Project period:** 2024-07-03 → 2026-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10920247

## Citation

> US National Institutes of Health, RePORTER application 10920247, Cribsy: A platform for home-based automated developmental risk screening (1R43HD115478-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10920247. Licensed CC0.

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