Pain Assessment

The Fifth Workshop on Automated Assessment of Pain

Monday, October 13rd, 2025
<click here for pdf>

9 h: Opening: Zakia Hammal, Steffen Walter, and Nadia Berthouze

9-10 h: Invited Talk

10-10.30 h: Coffee Break

10.30 h: Sai Revanth Reddy Boda et al.
Canonical Time Series Features for Pain Classification
10.45 h: Richard A. A. Jonker et al.
When Features Matter More than Sequence: A Case for Tabular In Context Learning in Pain Classification
11 h: Tahia Tazin et al.
Feel the Pain: An Interpretable Multimodal Approach for Physiological Signal-Based Pain Detection
11.15 h: Stefanos Gkikas et al.
Tiny-BioMoE: a Lightweight Embedding Model for Biosignal Analysis
11.30 h: Raul Fernandez Rojas et al.
The AI4Pain Grand Challenge 2025: Advancing Pain Assessment with Multimodal Physiological Signals
11.45 h: Anup Kumar Gupta et al.
PainXtract: A Multimodal System for Multiclass Pain Classification Using Physiological Signals

12-13.30 h: Lunch break

13.30 h: Javier Orlando Pinzon-Arenas et al.
A Multimodal Deep Learning Exploration for Pain Intensity Classification
13.45 h: Miguel Javierre et al.
Explaining Pain by Combining Deep Learning Models and Physiology-Driven Ensembles using PPG, EDA, and Respiration
14 h: Rupal Agarwal et al.
EnsembleIQ-Pain: Intelligent Cluster Calibration for Personalized Pain Detection
14.15 h: Sajeeb Datta et al.
Painthenticate: Feature Engineering on Multimodal Physiological Signals

14.30-15 h: Coffee Break

15 h: Anis Elebiary et al.
Investigation into Unimodal Versus Multimodal Pain Recognition from Physiological Signals
15.15 h: Stefanos Gkikas et al.
Efficient Pain Recognition via Respiration Signals: A Single Cross-Attention Transformer Multi-Window Fusion Pipeline
15.30 h: Stefanos Gkikas et al.
Multi-Representation Diagrams for Pain Recognition: Integrating Various Electrodermal Activity Signals into a Single Image

15.45-16 h: Closing