Dynamic Pain Analysis and Prediction of Chronicity Using Physiological Signals

Abstract

Pain is one of the major health problems worldwide, significantly affecting patients’ quality of life. Although numerous studies have focused on the detection and prediction of pain, most of them are limited to binary classifications (Pain/No pain) of acute pain (immediate pain). However, there is another less-studied category —chronic pain— a persistent type of pain that is often ignored, which can range from being mildly uncomfortable to something far more serious than a harmless ache.
This project aims to identify the most significant and sensitive features related to pain that can help predict, with greater accuracy and low computational cost, a possible chronification of pain based on physiological changes across different intensity levels of the acute stage, using the BioVid Heat Pain database.