Detection of emotional states plays a prominent role in affective computing, decision-
making, and healthcare. Physiological signals are an ideal target for continuous and …

Since the existing music emotion classification researches focus on the single‐modal
analysis of audio or lyrics, the correlation among models are neglected, which lead to partial …

In this study, we evaluated the performance of tonic and phasic components of
Electrodermal activity (EDA) using machine learning algorithms for accurately recognizing …

Emotional intelligence strives to bridge the gap between human and machine interactions.
The application of such systems varies and is becoming more prominent as healthcare …

Emotions play an essential role in human life as they are linked to well-being and markers of
various diseases. Physiological signals can be used to assess emotions objectively and …

Automatic, cost-effective, and reliable cognitive workload estimation (CWE) is one of the
important issues in diagnosis and treatment of neurocognitive diseases, cognitive …

The experience of empathy for pain is underpinned by sensorimotor and affective
dimensions which, although interconnected, are at least in part behaviorally and neurally …

Accurate prediction and recognition of human emotions are crucial for effective human-
computer interfaces. An Automated Emotion Recognition (AER) method is highly desirable …

Automated emotion recognition using physiological signals has gained significant attention
in recent years due to its potential applications in human–computer interaction, healthcare …

The experience of empathy for pain is underpinned by sensorimotor and affective
dimensions which are behaviourally and neurally distinct. Spinal cord injuries (SCI) induce a …