AI conversational coach to deliver STEADI fall-prevention for older adults with and without mild cognitive impairment
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).
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.
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 ID | NIH-11370764 on NIH RePORTER |
What this research studies
You would interact with a friendly conversational agent (a virtual coach) that asks about your fall history, guides balance and strength activities, and reminds you about safety steps from the CDC STEADI program. The system is designed to work for community-living older adults and to adapt communication when someone has mild cognitive impairment. The project focuses on scaling this approach so more people can use it without large clinic visits, and it includes ways to share results with caregivers or clinicians. Participation likely involves using a tablet or phone app and occasionally connecting with a program team or partner organization.
Who could benefit from this research
Good fit: Ideal candidates are community-dwelling adults aged 65 and older, including those with mild cognitive impairment, who can use or have help using a tablet/phone and are concerned about falls.
Not a fit: People living in skilled nursing facilities, those with advanced dementia who cannot engage with a virtual coach, or those without access to the required device or internet may not benefit from this program.
Why it matters
Potential benefit: If successful, this could make proven fall-prevention care easier to use and more widely available, lowering falls, injuries, and related hospital visits.
How similar studies have performed: Multifactorial programs based on STEADI have reduced fall risk in prior work, and digital/telehealth fall programs show promise, but using a conversational relational agent to scale STEADI is a relatively new combination.
Where this research is happening
Millbrae, United States
- Friendi.fi Corporation — Millbrae, United States (Active)
Researchers
- Principal investigator: Kerssens, Chantal M — Friendi.fi Corporation
- Study coordinator: Kerssens, Chantal M
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 below.