Eye behaviour provides valuable information revealing one's higher cognitive functions and
state of affect. Although eye tracking is gaining ground in the research community, it is not …

Objective. Processing strategies are analyzed with respect to the classification of
electroencephalographic signals related to brain-computer interfaces (BCIs) based on motor …

We present a new dataset and benchmark with the goal of advancing research in the
intersection of brain activities and eye movements. Our dataset, EEGEyeNet, consists of …

Abstract Background and Objective: The cognitive workload is an important component in
performance psychology, ergonomics, and human factors. Publicly available datasets are …

Eye tracking systems have greatly improved in recent years, being a viable and affordable
option as digital communication channel, especially for people lacking fine motor skills …

Background Phase synchrony has extensively been studied for understanding neural
coordination in health and disease. There are a few studies concerning the implications in …

Objective This study addresses the challenge of user-specific bias in Brain-Computer
Interfaces (BCIs) by proposing a novel methodology. The primary objective is to employ a …

Objective. Graph signal processing (GSP) concepts are exploited for brain activity decoding
and particularly the detection and recognition of a motor imagery (MI) movement. A novel …

Abstract Autism Spectrum Disorder (ASD) is a neurological condition that is challenging to
diagnose. Numerous studies demonstrate that children diagnosed with autism struggle with …

Graph signal processing (GSP) provides signal analytic tools for data defined in irregular
domains, as is the case of non-invasive electroencephalography (EEG). In this work, the …