Multi-Representation Diagrams for Pain Recognition: Integrating Various Electrodermal Activity Signals into a Single Image

TL;DR

This paper introduces a novel multi-representation diagram approach for pain recognition using electrodermal activity signals, effectively integrating various signal representations into a single image to improve assessment accuracy.

Contribution

It presents a new pipeline that visualizes multiple electrodermal activity signal representations jointly, offering a robust alternative to traditional fusion methods for pain assessment.

Findings

Achieves comparable or superior results to traditional fusion methods

Demonstrates effectiveness across diverse processing and filtering techniques

Provides a unified visualization approach for multimodal signals

Abstract

Pain is a multifaceted phenomenon that affects a substantial portion of the population. Reliable and consistent evaluation supports individuals experiencing pain and enables the development of effective and advanced management strategies. Automatic pain-assessment systems provide continuous monitoring, guide clinical decision-making, and aim to reduce distress while preventing functional decline. Incorporating physiological signals allows these systems to deliver objective, accurate insights into an individual's condition. This study has been submitted to the Second Multimodal Sensing Grand Challenge for Next-Gen Pain Assessment (AI4PAIN). The proposed method introduces a pipeline that employs electrodermal activity signals as the input modality. Multiple signal representations are generated and visualized as waveforms, which are then jointly presented within a unified multi-representation diagram. Extensive experiments using diverse processing and filtering techniques, along with various representation combinations, highlight the effectiveness of the approach. It consistently achieves comparable and, in several cases, superior results to traditional fusion methods, positioning it as a robust alternative for integrating different signal representations or modalities.