Using algorithms to analyze movement data for recovery after wrist fractures
Official title: Algorithmic Analyses of Accelerometry Data to Capture Meaningful Upper Extremity Use and Recovery Following Distal Radius Fracture Repair
Funded at Medstar Health Research Institute · NIH-11054086 · Data updated 2026-11-12
This study is looking at how smart technology can track your arm movements while you recover from a wrist fracture, helping doctors understand your healing better and make more informed treatment choices.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Medstar Health Research Institute NIH-funded |
| Lab location | 1 site (Hyattsville, United States) |
| Project start | September 19, 2024 |
| Project end | August 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $388,960 |
| NIH project number | 1R21AR083674-01A1 |
| Project ID | NIH-11054086 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are older women who have experienced a distal radius fracture and are undergoing treatment.
✕Less likely to help
Patients with wrist fractures who are not able to participate in accelerometer monitoring or those with other complicating health conditions may not benefit from this research.
What this research studies
This research investigates how advanced machine learning algorithms can analyze data from accelerometers worn on the wrist to better understand how patients use their arms during recovery from distal radius fractures. By capturing detailed movement patterns in both controlled environments and at home, the study aims to provide insights into functional recovery that traditional methods may miss. The goal is to improve treatment decisions by offering a more nuanced view of upper extremity use and recovery.
Why it matters
Potential benefit: If successful, this research could lead to more personalized and effective rehabilitation strategies for patients recovering from wrist fractures.
How similar studies have gone: While the use of machine learning in analyzing movement data is a growing field, this specific application to wrist fracture recovery is relatively novel and has not been extensively tested.
Where this research is happening
-
Medstar Health Research Institute
Hyattsville, United States Active
Researchers
- Principal investigator: Giladi, Aviram Moshe — Medstar Health Research Institute
- Study coordinator: Giladi, Aviram Moshe
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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.