Smartwatch system to better measure children's hyperactivity
Official title: Using Machine Learning and Sensing to Contextualize Hyperactivity Measurement on Wearable Devices
Funded at Nurelm E-Business Software · NIH-11169947 · Data updated 2026-11-12
A smartwatch-based system that tracks activity to help measure hyperactivity in children with ADHD.
Quick facts
| Grant type | Sbir 2 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Nurelm E-Business Software NIH-funded |
| Lab location | 1 site (Pittsburgh, United States) |
| Project start | August 15, 2024 |
| Project end | August 14, 2027 |
| Funding year | 2025 |
| Award (this year) | $590,540 |
| NIH project number | 5R44MH138145-02 |
| Project ID | NIH-11169947 on NIH RePORTER |
Who could benefit from this research
✓Could help
Children with an ADHD diagnosis (caregiver consent required) who can wear a smartwatch and whose caregivers can support device use and data sharing.
✕Less likely to help
Children who cannot tolerate wearing a watch, who are primarily inattentive without hyperactivity, or who have movement-limiting conditions may not benefit from this approach.
What this research studies
If your child takes part, they would wear a smartwatch that passively collects movement and environment information. The device sends data to a secure server where machine learning tries to recognize the child's setting (for example, classroom versus playground) and put motion into context. The team will compare activity on days your child is on medication versus off medication in both short standardized tests and everyday life. This pilot checks whether the system can give quick, objective feedback about hyperactivity that could help doctors and researchers.
Why it matters
Potential benefit: Could give more objective, real‑time information about hyperactivity to help guide medication decisions and measure treatment response.
How similar studies have gone: Traditional actigraphy has been used before, but combining modern smartwatch sensors with machine learning to detect context is a newer approach with limited pilot evidence so far.
Where this research is happening
-
Nurelm E-Business Software
Pittsburgh, United States Active
Researchers
- Principal investigator: Shaaban, Sami — Nurelm E-Business Software
- Study coordinator: Shaaban, Sami
Related research
Other NIH-funded projects on the same topics.
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LemurDx: smarter wearables to measure hyperactivity in children with ADHD
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Measuring hyperactivity in children using smartwatches and machine learning.
This study is testing a new smartwatch system called LemurDx that helps track how active children with ADHD are in different places, like school or the playground, to better understand how their medication is working and improve their treatment.
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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.