Does the Heart Show Your Pain? Tackling the X-ITE Pain Challenge with Self-Supervised ECG Representation Learning

Excerpt

arXiv:2608.14662v1 Announce Type: cross Abstract: Accurate recognition of pain using physiological signals remains a challenging problem due to pain's subjective nature and high inter-individual variability. In this study, we investigate self-supervised representation learning (SSL) methods applied to unimodal electrocardiogram (ECG), complemented by multimodal pretraining, including accelerometer (ACC) signals from the chest. We focus on classifying low versus medium pain levels on the X-ITE Pa