Using a Conversational AI to Help Older Adults Prevent Falls at Home
Official title: Implementing and Scaling the STEADI Fall Prevention Algorithm Using a Conversational Relational Agent for Community-Dwelling Older Adults with and without Mild Cognitive Impairment (MCI).
Funded at Friendi.fi Corporation · NIH-11418945 · Data updated 2026-11-12
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.
Quick facts
| Grant type | Sbir 2 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Friendi.fi Corporation NIH-funded |
| Lab location | 1 site (Millbrae, United States) |
| Project start | September 26, 2023 |
| Project end | May 31, 2029 |
| Funding year | 2026 |
| Award (this year) | $852,676 |
| NIH project number | 5R44AG085913-03 |
| Project ID | NIH-11418945 on NIH RePORTER |
Who could benefit from this research
✓Could help
Older adults aged 65 and above, including those with mild cognitive impairment, who live in the community and have access to the conversational AI tool.
✕Less likely to help
Individuals without access to or comfort with AI-based guidance, or those needing acute medical management not addressed by this program, may not benefit.
What this research studies
If you are an older adult or caregiver, this project aims to make fall-prevention guidance more accessible through a friendly chat assistant that works with your routine. It builds on the STEADI framework—screening, assessment, and personalized advice—delivered via an easy-to-use conversational agent. The goal is to reduce fall risk and related injuries by supporting adherence to proven preventive steps in day-to-day life. The approach focuses on scalable, user-friendly deployment in community settings to reach many seniors without heavy in-person resource use.
Why it matters
Potential benefit: If successful, it could lower fall risk and improve independence for older adults, including those with mild cognitive impairment.
How similar studies have gone: Previous STEADI-based approaches reduce fall risk when well-implemented, but scaling with AI-enabled coaching is still being explored.
Where this research is happening
-
Friendi.fi Corporation
Millbrae, United States Active
Researchers
- Principal investigator: Kerssens, Chantal M — Friendi.fi Corporation
- Study coordinator: Kerssens, Chantal M
Related research
Other NIH-funded projects on the same topics.
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AI conversational coach to deliver STEADI fall-prevention for older adults with and without mild cognitive impairment
An easy-to-use virtual coach will guide older adults, including those with mild memory problems, through the CDC's STEADI fall-prevention steps to help reduce falls and keep people safer at home.
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Technology to support thinking and social life for older adults with mild cognitive impairment
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Understanding how difficult social experiences affect memory and dementia risk in diverse twins
This project looks at how challenging social experiences might influence memory problems and the risk for Alzheimer's and related dementias in a diverse group of twins.
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Technology for Thinking Skills and Social Connections in Older Adults with Mild Cognitive Impairment
This project aims to create and test smart software that helps older adults with mild memory problems improve their daily activities and stay connected with others.
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Improving Neurological Health with Brain Training for Mild Cognitive Impairment (INHANCE-MCI)
A computer-based brain training program is being tested to help people with mild cognitive impairment maintain thinking skills and daily functioning.
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.