SmartGait: a smartphone AI tool to predict fall risk for older adults
Official title: SCH: SmartGait: Smartphone Video-Based AI for Personalized Fall Risk Assessment
Funded at Florida Atlantic University · NIH-11579063 · Data updated 2026-11-12
A smartphone app uses AI to analyze a simple gait test and predict when a person may fall, helping clinicians tailor prevention for older adults.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Florida Atlantic University NIH-funded |
| Lab location | 1 site (Boca Raton, United States) |
| Project start | September 1, 2026 |
| Project end | May 31, 2030 |
| Funding year | 2026 |
| Award (this year) | $305,735 |
| NIH project number | 1R01AG108198-01 |
| Project ID | NIH-11579063 on NIH RePORTER |
Who could benefit from this research
✓Could help
Older adults at risk of falling who can perform the Timed Up and Go test.
✕Less likely to help
Individuals unable to complete the Timed Up and Go assessment or without fall risk concerns may see limited benefit.
What this research studies
Falls are a major health problem for older adults, leading to ED visits and hospitalizations. This project turns a common test, the Timed Up and Go, into an AI-powered, smartphone-based assessment that can give personalized, time-specific fall-risk predictions. The goal is to replace costly lab tools with an accessible, scalable solution that clinicians can use in routine care. By delivering individualized risk information, it aims to enable timely and targeted interventions to prevent falls.
Why it matters
Potential benefit: If successful, the tool could help clinicians identify high-risk patients earlier and reduce fall-related injuries.
How similar studies have gone: Previous work shows promise for AI-based gait analysis, but this project seeks to enable time-specific, personalized predictions in a smartphone setting.
Where this research is happening
-
Florida Atlantic University
Boca Raton, United States Active
Researchers
- Principal investigator: Ghoraani, Behnaz — Florida Atlantic University
- Study coordinator: Ghoraani, Behnaz
Related research
Other NIH-funded projects on the same topics.
-
Reducing Fall Risk with Hip Hip Abductor Stimulation During Balance Training
This project tests whether using electrical stimulation on the hip abductors during balance training helps older veterans improve balance and reduce fall risk.
-
Real-life Dual-Task Training for Older Adults at Risk to Fall
A pilot program tests a six-week real-life dual-task training program to help older adults reduce fall risk while doing everyday activities.
-
Smartphone coaching to prevent falls after stroke and train researchers
A smartphone-based coaching tool is being developed to help stroke survivors move more safely and reduce fall risk, with training opportunities for students at a major technical university.
-
STEADI-based Fall Prevention in Assisted Living Facilities
A plan to test a step-by-step fall-prevention program in eight assisted living facilities to see if it reduces falls, how well it works in real settings, and whether it makes economic sense.
-
Preventing Falls in Older Adults Using Floor Vibrations to Detect Falls and Gait Changes
A new approach aims to detect falls and gait changes in people aged 65 and older by analyzing floor vibrations, with the goal of preventing injuries and reducing fall-related costs.
-
Using a Conversational AI to Help Older Adults Prevent Falls at Home
A small, practical project uses a chat-based AI coach to help people 65 and older follow proven steps to prevent falls, including those with mild cognitive impairment.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.