21 citations · 66 across the 20 of their papers we have counts for
8 papers · 1 filter
MUPAE: Multimodal Unified Perception with Asymmetric Attention for Emotion Assessment
Stefanos Gkikas, Eric Nichols, Christian Arzate Cruz +1
Automatic emotion assessment can benefit from combining neural and behavioral signals, but many multimodal approaches rely on separate, modality-specific feature-extraction pipelin…
A Multi-Scale Temporal Framework with Dynamic Fusion for EEG-Based Emotion Recognition
Stefanos Gkikas, Yang Guo, Guangliang Li +3
Mixed emotions represent a clinically relevant but still underexplored target for automatic emotion recognition. EEG provides millisecond-level access to neural activity, yet most…
Efficient and Interpretable Body-Based Emotion Recognition with Lightweight Temporal Convolutional Networks
Christian Arzate Cruz, Stefanos Gkikas, Houshyar Asadi
Body-based emotion recognition is important for real-time affective systems, but graph-based skeleton models can be computationally expensive. This paper studies whether lightweigh…
Efficient Pain Recognition via Respiration Signals: A Single Cross-Attention Transformer Multi-Window Fusion Pipeline
Stefanos Gkikas, Ioannis Kyprakis, Manolis Tsiknakis
Pain is a complex condition that affects a large portion of the population. Accurate and consistent evaluation is essential for individuals experiencing pain and supports the devel…
Multi-Representation Diagrams for Pain Recognition: Integrating Various Electrodermal Activity Signals into a Single Image
Stefanos Gkikas, Ioannis Kyprakis, Manolis Tsiknakis
Pain is a multifaceted phenomenon that affects a substantial portion of the population. Reliable and consistent evaluation supports individuals experiencing pain and enables the de…
Tiny-BioMoE: a Lightweight Embedding Model for Biosignal Analysis
Stefanos Gkikas, Ioannis Kyprakis, Manolis Tsiknakis
Pain is a complex and pervasive condition that affects a significant portion of the population. Accurate and consistent assessment is essential for individuals suffering from pain,…
A Pain Assessment Framework based on multimodal data and Deep Machine Learning methods
Stefanos Gkikas
From the original abstract: This thesis initially aims to study the pain assessment process from a clinical-theoretical perspective while exploring and examining existing automatic…
Multi-task Neural Networks for Pain Intensity Estimation using Electrocardiogram and Demographic Factors
Stefanos Gkikas, Chariklia Chatzaki, Manolis Tsiknakis
Pain is a complex phenomenon which is manifested and expressed by patients in various forms. The immediate and objective recognition of it is a great of importance in order to atta…