Background Virtual reality (VR) technologies are playing an increasingly important role in
the diagnostics and treatment of mental disorders. Objective To systematically review the …

Electroencephalography (EEG) has been a staple method for identifying certain health
conditions in patients since its discovery. Due to the many different types of classifiers …

Analysis of electroencephalogram (EEG) signals is essential because it is an efficient
method to diagnose neurological brain disorders. In this work, a single system is developed …

Rapid advancements in the medical field have drawn much attention to automatic emotion
classification from EEG data. People's emotional states are crucial factors in how they …

Background The traditional rehabilitation for neurological diseases lacks the active
participation of patients, its process is monotonous and tedious, and the effects need to be …

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with core
impairments in the social relationships, communication, imagination, or flexibility of thought …

Objective: To build group-level classification models capable of recognizing affective states
and mental workload of individuals with autism spectrum disorder (ASD) during driving skill …

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition which affects a
person's cognition and behaviour. It is a lifelong condition which cannot be cured completely …

Lack of communication causes problems for patients with neurodegenerative diseases, so
the need for alternative methods is required to convey their thoughts with caretakers, friends …

Abstract Current models on Explainable Artificial Intelligence (XAI) have shown a lack of
reliability when evaluating feature-relevance for deep neural biomarker classifiers. The …