Predicting falls in older adults using everyday walking patterns
Official title: Using instrumented everyday gait to predict falls in older adults using the WHS cohort
Funded at Brigham and Women's Hospital · NIH-11041100 · Data updated 2026-11-12
This study is looking at how the way older adults walk can help us understand their risk of falling, using special devices to track their movements over a week, so we can find those who might need extra support to stay safe.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Brigham and Women's Hospital NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | June 1, 2023 |
| Project end | February 28, 2027 |
| Funding year | 2025 |
| Award (this year) | $557,070 |
| NIH project number | 5R01AG078256-03 |
| Project ID | NIH-11041100 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are community-living older adults who are 21 years and older and may be at risk of falling.
✕Less likely to help
Patients who are not community-living or those who do not have access to wearable technology may not benefit from this research.
What this research studies
This research investigates how everyday walking patterns in older adults can help predict the risk of falls. By using wearable accelerometers, researchers will collect data on gait speed, cadence, and physical activity levels over a week. The goal is to identify individuals who are at higher risk of falling and could benefit from early interventions. This approach aims to improve fall prevention strategies by utilizing real-world data rather than traditional clinic-based assessments.
Why it matters
Potential benefit: If successful, this research could lead to better identification of older adults at risk of falls, allowing for timely interventions that could reduce injuries and improve quality of life.
How similar studies have gone: Previous research has shown promising results in using gait measures to predict falls, but this study aims to expand on those findings with a larger and more diverse population.
Where this research is happening
-
Brigham and Women's Hospital
Boston, United States Active
Researchers
- Principal investigator: Wayne, Peter Michael — Brigham and Women's Hospital
- Study coordinator: Wayne, Peter Michael
Related research
Other NIH-funded projects on the same topics.
-
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.
-
Wearable movement monitoring to spot fall risk in older adults
This project uses a small wearable sensor worn during daily life to find walking and activity patterns that help identify older adults who are more likely to fall.
-
Preventing injurious falls in older adults using floor vibration and gait monitoring
A floor-mounted vibration system aims to detect falls and changes in walking in older adults, including people with dementia, so help can arrive faster and injuries can be reduced.
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This study is all about helping people who have had a stroke improve their balance and lower their chances of falling by trying out new training methods that focus on specific balance issues.
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Movement-Enhanced Walking Training to Improve Balance After Stroke
A specialized treadmill training using a cable-driven device, called Movement Amplification Environment (MAE), helps people with chronic stroke improve walking balance by enhancing their own movement awareness.
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.