# Quantitative Assessment of Dental Pain using a smartphone-attachable electrodermal activity sensor

> **NIH NIH R21** · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · 2021 · $203,214

## Abstract

Project Summary/Abstract
Our long-term goal is to develop a personalized pain-control strategy for toothache, which is the primary
reason patients seek dental treatment. An objective and quantitative assessment of dental pain is essential to
develop efficient treatment for pain control. Diagnosing the source for toothache accurately is crucial as some
conditions not only can cause excruciating pain but even be life-threatening. Current dental pain diagnosis
relies fully on subjective responses from patients, which is problematic when patients are unable to
communicate such as young children and individuals with cognitive disorders or langauge problems.
Minimizing pain during and after dental treatment is another important concern for patients and dentists.
Numbness of lip and tongue is typically used as a sign of successful local anesthesia for teeth of the lower jaw.
This method is rather ineffective, as 30-40% of patients still experience pain during treatment. Furthermore, the
selection of painkillers is partially patient-driven, which can lead to the abuse of opiods. This exploratory project
aims to test whether electrodermal activity (EDA) can be used to assess dental pain objectively and reliably.
When we experience pain, our activity of the sympathetic nervous system (SNS) is increased. Although the
role of the SNS in dental pain is not fully understood, increased numbers of sympathetic nerve fibers have
been reported in the pulp of infected teeth. EDA devices measure skin conductance on fingers, which strongly
correlates to sweat production and exclusively mirrors acitivity of the SNS. When healthy teeth receive cold
and electrical stimulation, patients feel a sensation that recovers quickly. In our pilot study, such sensations
were highly correlated with EDA recordings using a time-varying index (TVSymp) algorithm, which we
developed. We thus hypothesize that the time-varying index (TVSymp) of EDA can reflect pulpal status and is
a sensitive and specific measure for dental pain. In this proposed study, we will develop a smartphone-based
miniaturized EDA system for data collection and analysis of TVSymp (Aim 1). This low-cost smartphone-based
EDA device could easily be used in clinical settings and for wireless reporting of pain levels from a patient’s
home, for example after surgery, to better adjust pain medication. It may also enhance compliance of
participants in future clinical pain studies. We will determine whether TVSymp can reliably be used to diagnose
pulpal status and assess levels of dental pain using the existing large-sized EDA device as well as the
smartphone-based device once ready to use (Aim 2). If successful, TVSymp recordings would improve the
accuracy of pulpal diagnosis and be a novel biomarker for dental pain to replace subjective pain reporting.
This project is conceptually and technically novel because: 1) the activity of SNS has never been used for pulp
diagnosis and assessing dental pain; 2) the TVSymp index is ...

## Key facts

- **NIH application ID:** 10171570
- **Project number:** 5R21DE029563-02
- **Recipient organization:** UNIVERSITY OF CONNECTICUT SCH OF MED/DNT
- **Principal Investigator:** I-Ping Chen
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $203,214
- **Award type:** 5
- **Project period:** 2020-06-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10171570

## Citation

> US National Institutes of Health, RePORTER application 10171570, Quantitative Assessment of Dental Pain using a smartphone-attachable electrodermal activity sensor (5R21DE029563-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10171570. Licensed CC0.

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