Background Hand rehabilitation is core to helping stroke survivors regain activities of daily
living. Recent studies have suggested that the use of electroencephalography-based brain …

Epilepsy is a chronic neurological disorder with a comparatively high prevalence rate. It is a
condition characterized by repeated and unprovoked seizures. Seizures are managed with …

Electroencephalography (EEG), as a non-invasive modality, enables the representation of
the underlying neuronal activities as electrical signals with high temporal resolution. In …

Collecting emotional physiological signals is significant in building affective Human-
Computer Interactions (HCI). However, how to evoke subjects' emotions efficiently in EEG …

This paper proposes emotion detection using Electroencephalography (EEG) signal based
on Linear Formulation of Differential Entropy (LF-D f E) feature extractor and BiLSTM …

Motion artifact is observed in electroencephalogram (EEG) signals during the acquisition.
The elimination of this type of artifact using various signal processing approaches is …

Electroencephalography (EEG) signals are often contaminated with artifacts. It is imperative
to develop a practical and reliable artifact removal method to prevent the misinterpretation of …

Affective human-robot interaction is still an active area of research in part due to the great
advances in artificial intelligence. Now, the design of autonomous devices that work in real …

Social advertising is designed to have an impact on the behavior of the target audience to
improve the welfare of both the individuals and the society. The challenge for social …

Background The EEG-based emotion recognition is one of the primary research orientations
in the field of emotional intelligence and human-computer interaction (HCI). New method We …