11 papers
MUPAS: Multimodal Unified Perception with Asymmetric Attention for Stress Assessment
Stefanos Gkikas, Thomas Kassiotis, Yu Fang +8
Stress is a leading contributor to long-term physical and mental health decline. The automatic assessment of stress is a promising approach for continuous monitoring and mitigating…
Towards a Unified Modality-Agnostic Multimodal Framework for Cognitive Workload Assessment
Stefanos Gkikas, Christian Arzate Cruz, Calvin Joseph +2
Cognitive workload reflects the mental effort required during task performance and is central to the design of adaptive human-machine systems. The use of biosignals to measure cogn…
UNWIND: Any-Length Facial Video for Stress Detection without Temporal Windowing
Stefanos Gkikas, Christian Arzate Cruz, Eric Nichols +2
Automatic stress recognition from facial video provides a non-contact approach for affective monitoring. However, most existing video-based methods divide complete recordings into…
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…
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…
ReFace: Reorganizing Facial Spatiotemporal Representations for Improved Pain Assessment
Stefanos Gkikas, Yu Fang, Christian Arzate Cruz +2
Automatic pain assessment from facial video remains challenging due to the spatial heterogeneity of pain-related facial cues. This study proposes ReFace, a spatial reorganization p…
A Unified Tokenization Framework for Pain Recognition using Heterogeneous 3D Modalities
Stefanos Gkikas, Christian Arzate Cruz, Valentina Becchetti +3
Pain is a complex and pervasive phenomenon affecting a large percentage of the population, and accurate assessment is essential for effective clinical management and intervention.…
One-Block Transformer (1BT) for EEG-Based Cognitive Workload Assessment
Stefanos Gkikas, Christian Arzate Cruz, Thomas Kassiotis +3
Accurate and continuous estimation of cognitive workload is fundamental to creating adaptive human-machine systems. However, designing architectures that balance representational c…
A Lightweight Transformer for Pain Recognition from Brain Activity
Stefanos Gkikas, Christian Arzate Cruz, Yu Fang +6
Pain is a multifaceted and widespread phenomenon with substantial clinical and societal burden, making reliable automated assessment a critical objective. This paper presents a lig…
Efficient Emotion-Aware Iconic Gesture Prediction for Robot Co-Speech
Edwin C. Montiel-Vazquez, Christian Arzate Cruz, Stefanos Gkikas +3
Co-speech gestures increase engagement and improve speech understanding. Most data-driven robot systems generate rhythmic beat-like motion, yet few integrate semantic emphasis. To…
When and How to Express Empathy in Human-Robot Interaction Scenarios
Christian Arzate Cruz, Edwin C. Montiel-Vazquez, Chikara Maeda +1
Incorporating empathetic behavior into robots can improve their social effectiveness and interaction quality. In this paper, we present whEE (when and how to express empathy), a fr…