The market uptake of Brain-Computer Interface technologies for clinical and non-clinical
applications is attracting the scientific world towards the development of daily-life wearable …

An interesting case of the well-known Dataset Shift Problem is the classification of
Electroencephalogram (EEG) signals in the context of Brain-Computer Interface (BCI). The …

Electroencephalography (EEG) sensor plays an important role in developing brain-computer
interfaces (BCI) to enhance human-computer interaction (HCI). Nowadays, various types of …

Emotions play an important role in everyday life and contribute to physical and mental
health. Emotional states can be detected by electroencephalography (EEG signals). Efficient …

Background For non-invasive brain-computer interface systems (BCIs) with multiple
electroencephalogram (EEG) channels, the key factor limiting their convenient application in …

Emotions play an important role in everyday life and contribute to physical and emotional
well-being. They can be identified by verbal or non-verbal signs. Emotional states can be …

Efficient information retrieval from the EEG sensors is a complex and challenging task,
particularly in the context of psychology, including emotional states. Therefore, different …

In this paper, the topic of detection of outliers in EEG signals was discussed, which facilitates
making decisions about the diagnosis of a patient based on this study. We used two …

Over the past decade, outlier detection has become a prominent area of research. Much of
the current literature on Knowledge Discovery in Databases (KDD) pays particular attention …

Quantitative measurement of pain using the Electroencephalogram (EEG) signals has
received much attention, recently. Pain EEG data processing is associated with complexity …