Previous studies on emotion recognition from electroencephalography (EEG) mainly rely on single-channel-based feature extraction methods, which ignore the functional connectivity between brain regions. Hence, in this paper, we propose a novel emotion...
Domain adaptation (DA) tackles the problem where data from the source domain and target domain have different underlying distributions. In cross-domain (cross-subject or cross-dataset) emotion recognition based on EEG signals, traditional classificat...
Emotion recognition using Artificial Intelligence (AI) is a fundamental prerequisite to improve Human-Computer Interaction (HCI). Recognizing emotion from Electroencephalogram (EEG) has been globally accepted in many applications such as intelligent ...
Besides facial or gesture-based emotion recognition, Electroencephalogram (EEG) data have been drawing attention thanks to their capability in countering the effect of deceptive external expressions of humans, like faces or speeches. Emotion recognit...
The theory of modern organizations considers emotional intelligence to be the metric for tools that enable organizations to create a competitive vision. It also helps corporate leaders enthusiastically adhere to the vision and energize organizational...
Emotion is interpreted as a psycho-physiological process, and it is associated with personality, behavior, motivation, and character of a person. The objective of affective computing is to recognize different types of emotions for human-computer inte...
Decades of neurobiological research have disclosed the diverse manners in which the response properties of neurons are dynamically modulated to support adaptive cognitive functions. This neuromodulation is achieved through alterations in the biophysi...
In this work, an attempt has been made to classify emotional states using electrodermal activity (EDA) signals and multiscale convolutional neural networks. For this, EDA signals are considered from a publicly available "A Dataset for Emotion Analysi...
Emotion recognition based on electroencephalograms has become an active research area. Yet, identifying emotions using only brainwaves is still very challenging, especially the subject-independent task. Numerous studies have tried to propose methods ...
Sleep arousals are transient periods of wakefulness punctuated into sleep. Excessive sleep arousals are associated with symptoms such as sympathetic activation, non-restorative sleep, and daytime sleepiness. Currently, sleep arousals are mainly annot...
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