Using a wearable device to tell apart dental pain from stress
Official title: Diagnose and Differentiate Dental Pain from Stress Using a Wearable Electrodermal Activity Device
Funded at University of Connecticut Storrs · NIH-10995731 · Data updated 2026-11-12
This study is looking at how a special wearable device can help tell the difference between dental pain and stress by measuring skin responses, which could lead to better ways to diagnose and treat your dental issues.
Quick facts
| Grant type | Fellowship grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Connecticut Storrs NIH-funded |
| Lab location | 1 site (Storrs-Mansfield, United States) |
| Project start | December 1, 2024 |
| Project end | November 30, 2027 |
| Funding year | 2024 |
| Award (this year) | $80,556 |
| NIH project number | 1F32DE033566-01A1 |
| Project ID | NIH-10995731 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include adults and children experiencing dental pain or stress related to dental procedures.
✕Less likely to help
Patients who do not experience dental pain or stress, or those with severe communication issues that prevent participation, may not benefit from this research.
What this research studies
This research investigates how a wearable electrodermal activity (EDA) device can help distinguish between dental pain and stress responses in patients. By measuring skin conductance, the device aims to provide objective data on pain levels, which is crucial since both dental pain and stress can trigger similar physiological responses. The study will utilize skin nerve activity (SKNA) signals recorded from ECG to accurately identify when pain occurs, allowing for better diagnosis and treatment. Machine learning techniques will be applied to analyze the data collected from participants, enhancing the understanding of pain mechanisms.
Why it matters
Potential benefit: If successful, this research could lead to more accurate diagnoses of dental pain, improving treatment outcomes for patients.
How similar studies have gone: While the use of EDA in pain assessment is established, the specific approach of combining SKNA with machine learning for differentiating dental pain from stress is relatively novel.
Where this research is happening
-
University of Connecticut Storrs
Storrs-Mansfield, United States Active
Researchers
- Principal investigator: Kong, Youngsun — University of Connecticut Storrs
- Study coordinator: Kong, Youngsun
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.