Automatic Pain Intensity Estimation based on Electrocardiogram and Demographic Factors

Abstract

Automatic pain intensity estimation possess significant importance for reliable and complete pain management. The accurate and continuous monitoring is essential in order to attain objective insight about the condition of the patient. In this work, we elaborate physiological signals in order to estimate the pain intensity and investigate the impact of demographic factors. Specifically, we exploit electrocardiography signals, adopting the Pan-Tompkins algorithm to extract important features and apply well-validated classification methods, while we explore the correlation of gender and age with the pain manifestation.