Female-male Differences Should be Considered in Physical Pain Quantification based on Electrodermal Activity: Preliminary Study.

Abstract

Objective pain quantification is an important but difficult goal. Electrodermal activity (EDA) has been widely explored for this purpose, given its reported sensitivity to pain. However, cognitive stress can hinder successful estimation of physical pain when using EDA signals. We collected EDA signals from ten subjects (5 male and 5 female) undergoing pain stimulation, and calculated phasic, tonic, and frequency-domain features. Each subject experienced pain with and without stress. Three low and three high pain sessions were induced using two thermal grills (low-level for visual analog scale [VAS] 4 or 5 and high-level for VAS 7 or more). The Stroop test was performed for inducing cognitive stress. Significant differences between EDA features of painless and pain segments were observed. Significant differences between no pain and stress were also observed. Furthermore, we compared differences in EDA features between females and males under pain and cognitive stress. Frequency-domain EDA features of pain increased with stress for both females and males. Frequency-domain features derived from females also showed higher standard deviation than did those derived from males. We performed machine learning analysis and evaluated the models using leave-one-subject-out cross-validation. We obtained balanced accuracies of 63.5%, 72.4%, and 53.2% (combined, male, and female) when using training data of the same sex and 47.6%, 57.4%, and 42.7% (combined, male, and female) when using different sex for training.Clinical Relevance-Our preliminary results suggest that sex of patients should be considered to increase the accuracy of pain quantification based on EDA in the presence of cognitive stress.