# AVA_ AI Video-Based Mobile Application for Reliable, Accessible, and Low-Cost Fall Risk Assessments of Older Adults

> **NIH NIH R43** · FORESIGHTCARES INC. · 2024 · $400,000

## Abstract

Abstract
Falls are a significant issue for older adults, causing physical, emotional, and financial strain. Research indicates that
regular and early fall screenings can reduce fall incidents and their severity. However, this test usually requires
supervision by healthcare professionals, limiting its accessibility, especially in underserved and rural areas. Current
technologies are often costly, invasive, and complicated to use independently, with many relying on self-reported data and
needing professional oversight for comprehensive fall risk assessment.
ForesightCares presents AVA as the first AI-powered, video-based mobile app for reliable at-home fall risk assessment.
AVA, a software-only solution, uses built-in cameras and CPU processing capabilities of smartphones for intelligent
processing. It is primarily designed for caregivers of older adults, including family members and staff in Independent
Living communities, to perform the assessment. AVA differentiates itself by using AI to assess gait, balance, and strength,
aligning with CDC guidelines. Its deep learning-based visual mobility assessment technology operates entirely on-device,
enhancing privacy and accessibility while avoiding external servers or cloud reliance. This makes AVA more accessible
and affordable for a broader range of users. However, the current version of AVA still requires validation and
customization for independent use in older adult living environments.
This Phase I study aims to validate AVA’s AI and evaluate its feasibility and acceptance as an effective video-based app
for routine fall risk assessment of older adults. The AVA will not be used as an intervention tool or a diagnosis app;
instead, it is solely used as a home assessment app for fall risk. Our approach focuses on rigorous validation on older
adults and studying and optimizing it for independent use by their caregivers. Our multifaceted team is a blend of AI and
computer vision specialists, software engineers, UX experts centered on human-driven design, senior community wellness
directors, physical therapists well-versed in fall risk assessment, and geriatricians. This project also proposes a close
partnership and collaboration with Wingate University and the North Carolina Department of Health and Human Services.
We will undertake a comprehensive validation and AI fine-tuning against high-end motion capture systems for accurate
and reliable assessment in a lab setting (through a collaboration with Wingate University) and 100 diverse older adult
participants. By bringing recent advances in large language models and self-supervised pre-trained models, we aim to
make AVA a perspective-invariant assessment app to achieve reliable measurements while relaxing the setup requirements
for independent at-home assessment. This project also aims to perform comprehensive user experience research and
usability studies in a controlled environment, involving 50 older adults from a wide range of demographics, includ...

## Key facts

- **NIH application ID:** 11005668
- **Project number:** 1R43AG090129-01
- **Recipient organization:** FORESIGHTCARES INC.
- **Principal Investigator:** hamed tabkhi
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $400,000
- **Award type:** 1
- **Project period:** 2024-09-15 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11005668

## Citation

> US National Institutes of Health, RePORTER application 11005668, AVA_ AI Video-Based Mobile Application for Reliable, Accessible, and Low-Cost Fall Risk Assessments of Older Adults (1R43AG090129-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/11005668. Licensed CC0.

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