Emotions play a pivotal role in human cognition, exerting influence across diverse domains
of individuals' lives. The widespread adoption of artificial intelligence and machine learning …

Psychological studies have shown that Micro Gestures (MG) are closely linked to human
emotions. MG-based emotion understanding has attracted much attention because it allows …

Neural networks excel at capturing local spatial patterns through convolutional modules, but
they may struggle to identify and effectively utilize the morphological and amplitude periodic …

Deep learning techniques have drawn considerable interest in emotion recognition due to
recent technological developments in healthcare analytics. Automatic patient emotion …

The recognition of affective states is important for regulating stress levels and maintaining
mental health, and it is known that affective states can be inferred from physiological signals …

The development of transformer-based models has resulted in significant advances in
addressing various vision and NLP-based research challenges. However, the progress …

In the context of urban sustainable development and the creation of pedestrian-friendly
campus environments, optimizing campus walking spaces has emerged as a central focus …

This study aimed to propose a portable and intelligent rehabilitation evaluation system for
digital stroke-patient rehabilitation assessment. Specifically, the study designed and …

Traditional approaches for emotion recognition utilize unimodal physiological signals. The
effectiveness of such systems is affected by some limitations. To overcome them, this paper …

Most human emotion recognition methods largely depend on classifying stereotypical facial
expressions that represent emotions. However, such facial expressions do not necessarily …