Measuring hyperactivity in children using smartwatches and machine learning.
Using Machine Learning and Sensing to Contextualize Hyperactivity Measurement on Wearable Devices
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.
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 ID | NIH-11004217 on NIH RePORTER |
What this research studies
This research focuses on developing a software system called LemurDx that utilizes advanced sensor technology in smartwatches to measure hyperactivity in children diagnosed with ADHD. The system collects data passively from the smartwatch sensors and uses machine learning algorithms to analyze the context of the child's activity, distinguishing between different environments like classrooms and playgrounds. By providing objective measurements of hyperactivity, this research aims to enhance the assessment of medication effects in clinical trials and improve treatment outcomes for children with ADHD.
Who could benefit from this research
Good fit: Ideal candidates for this research are children aged 0-11 years who have been diagnosed with ADHD.
Not a fit: Patients who do not have ADHD or are outside the age range of 0-11 years may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could provide a more accurate and objective way to assess hyperactivity in children, leading to better treatment strategies for ADHD.
How similar studies have performed: Similar research using wearable technology and machine learning has shown promise in improving behavioral assessments, indicating that this approach could be effective.
Where this research is happening
Pittsburgh, United States
- Nurelm E-Business Software — Pittsburgh, United States (Active)
Researchers
- Principal investigator: Shaaban, Sami — Nurelm E-Business Software
- Study coordinator: Shaaban, Sami
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.