Review of eye tracking metrics involved in emotional and cognitive processes
V Skaramagkas, G Giannakakis… - IEEE Reviews in …, 2021 - ieeexplore.ieee.org
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 …
state of affect. Although eye tracking is gaining ground in the research community, it is not …
How to successfully classify EEG in motor imagery BCI: a metrological analysis of the state of the art
Objective. Processing strategies are analyzed with respect to the classification of
electroencephalographic signals related to brain-computer interfaces (BCIs) based on motor …
electroencephalographic signals related to brain-computer interfaces (BCIs) based on motor …
[HTML][HTML] COLET: A dataset for COgnitive workLoad estimation based on eye-tracking
E Ktistakis, V Skaramagkas, D Manousos… - Computer Methods and …, 2022 - Elsevier
Abstract Background and Objective: The cognitive workload is an important component in
performance psychology, ergonomics, and human factors. Publicly available datasets are …
performance psychology, ergonomics, and human factors. Publicly available datasets are …
EEGEyeNet: a simultaneous electroencephalography and eye-tracking dataset and benchmark for eye movement prediction
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 …
intersection of brain activities and eye movements. Our dataset, EEGEyeNet, consists of …
Improving user experience of eye tracking-based interaction: Introspecting and adapting interfaces
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 …
option as digital communication channel, especially for people lacking fine motor skills …
Exploiting the heightened phase synchrony in patients with neuromuscular disease for the establishment of efficient motor imagery BCIs
Background Phase synchrony has extensively been studied for understanding neural
coordination in health and disease. There are a few studies concerning the implications in …
coordination in health and disease. There are a few studies concerning the implications in …
Connectivity steered graph Fourier transform for motor imagery BCI decoding
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 …
and particularly the detection and recognition of a motor imagery (MI) movement. A novel …
Covariation informed graph Slepians for motor imagery decoding
K Georgiadis, DA Adamos… - … on Neural Systems …, 2021 - ieeexplore.ieee.org
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 …
domains, as is the case of non-invasive electroencephalography (EEG). In this work, the …
Involution fused convolution for classifying eye-tracking patterns of children with Autism Spectrum Disorder
Abstract Autism Spectrum Disorder (ASD) is a neurological condition that is challenging to
diagnose. Numerous studies demonstrate that children diagnosed with autism struggle with …
diagnose. Numerous studies demonstrate that children diagnosed with autism struggle with …
[HTML][HTML] Study of an Optimization Tool Avoided Bias for Brain-Computer Interfaces Using a Hybrid Deep Learning Model
NI Ajali-Hernández, CM Travieso-González… - IRBM, 2024 - Elsevier
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 …
Interfaces (BCIs) by proposing a novel methodology. The primary objective is to employ a …