In-home 3D sensor system to spot falls without wearables
Official title: Using Structured Light Sensing with Machine Learning to Detect Unwitnessed In-Home Falls
Funded at Applied Universal Dynamics Corporation · NIH-11177677 · Data updated 2026-11-12
This project builds a small, unobtrusive 3D sensor and smart software to automatically detect when older adults fall at home and trigger alerts when they cannot use a wearable button.
Quick facts
| Grant type | Sbir 2 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Applied Universal Dynamics Corporation NIH-funded |
| Lab location | 1 site (Loretto, United States) |
| Project start | February 15, 2020 |
| Project end | August 31, 2026 |
| Funding year | 2025 |
| Award (this year) | $789,449 |
| NIH project number | 5R44AG066263-04 |
| Project ID | NIH-11177677 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are adults aged 65 or older, especially those living alone or with mild to moderate memory problems who may forget to wear or press emergency pendants.
✕Less likely to help
People who live in nursing homes or assisted-living facilities with existing monitored systems, or those who do not want in-home sensors for privacy reasons, may not benefit from this system.
What this research studies
From my perspective as someone living at home, this system uses a structured light 3D sensor that makes a point-cloud picture of a room and machine learning that learns the motion patterns of falls. The device sits quietly in the home and does not require me to wear anything or push a button. When the software detects a likely fall, it can send an alert so help can arrive sooner. The project builds on earlier (phase I) tests and focuses on making the system reliable, low-cost, and easy to install in real homes.
Why it matters
Potential benefit: If successful, the system could get help to fallen older adults faster, reducing complications from long periods on the floor and possibly lowering injury-related costs.
How similar studies have gone: Related camera- and depth-sensor fall-detection projects have shown promising results in lab and limited home pilots, but large-scale, real-world in-home testing is still fairly limited.
Where this research is happening
-
Applied Universal Dynamics Corporation
Loretto, United States Active
Researchers
- Principal investigator: Gibson, Paul — Applied Universal Dynamics Corporation
- Study coordinator: Gibson, Paul
Related research
Other NIH-funded projects on the same topics.
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Falls and brain changes in older adults who don’t yet show dementia
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Lighting-centered home changes to prevent falls for people who are visually impaired
A study will test whether brighter, better-lit homes with fewer glare and clearer hazards reduce falls and help with daily tasks for people with vision loss.
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New balance training to prevent falls in older adults
A new, low-cost balance training program for people 65 and older aims to reduce the chance of falls by improving fast recovery after a trip.
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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.
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In-Home Sensory Training Therapy to Reduce Falls in Older Adults
A home-based program using stroboscopic eyewear to help older adults improve balance and reduce their risk of falls.
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Sleep, nighttime oxygen, and risk of falls and fractures in older adults
This study looks at how nocturnal low oxygen during sleep relates to falls and bone fractures in men and women aged 50 and older.
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.