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

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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 more sensitive and more consistent compared to other EDA indices used in previous pain assessment studies. Findings from this study have a great potential to significantly impact dental care and dental pain research.