Schizophrenia (SZ) is a devastating mental disorder that disrupts higher brain functions like
thought, perception, etc., with a profound impact on the individual's life. Deep learning (DL) …

The electroencephalogram (EEG) is an excellent tool for probing neural function, both in
clinical and research environments, due to its low cost, non-invasive nature, and …

Around a third of the total population of Europe suffers from mental disorders. The use of
electroencephalography (EEG) together with Machine Learning (ML) algorithms to diagnose …

Brain monitoring combined with automatic analysis of EEGs provides a clinical decision
support tool that can reduce time to diagnosis and assist clinicians in real-time monitoring …

This paper presents the theoretical and practical fundamentals of using physiology sensors
to capture human emotion reactivity in a products or systems engineering context. We aim to …

Overinterpretation of EEG is an important contributor to the misdiagnosis of epilepsy. For the
EEG to have a high diagnostic value and high specificity, it is critical to recognize waveforms …

Interpretation of electroencephalogram (EEG) signals can be complicated by obfuscating
artifacts. Artifact detection plays an important role in the observation and analysis of EEG …

Sensor-level human brain activity is studied during real and imaginary motor execution
using functional near-infrared spectroscopy (fNIRS). Blood oxygenation and deoxygenation …

The current evolution of 'cloud neuroscience'leads to more efforts with the large-scale EEG
applications, by using EEG pipelines to handle the rapidly accumulating EEG data …

Feature extraction for automatic classification of EEG signals typically relies on time
frequency representations of the signal. Techniques such as cepstral-based filter banks or …