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 …

Electroencephalogram (EEG) measures the neuronal activities in the form of electric
currents that are generated due to the synchronized activity by a group of specialized …

Diabetes is a major metabolic disorder which can affect entire body system adversely.
Undiagnosed diabetes can increase the risk of cardiac stroke, diabetic nephropathy and …

Electroencephalogram (EEG)-based major depressive disorder (MDD) machine learning
detection models can objectively differentiate MDD from healthy controls but are limited by …

Background Major depressive disorder (MDD) is a prevalent mental illness that is diagnosed
through questionnaire-based approaches; however, these methods may not lead to an …

Depression is a global psychological disease that does serious harm to people. Traditional
diagnostic method of the doctor-patient communication, is not objective and accurate …

Functional connectivity and effective connectivity of the human brain, representing statistical
dependence and directed information flow between cortical regions, significantly contribute …

Background and purpose In recent years, the development of machine learning (ML)
frameworks for automatic diagnosis of unipolar depression has escalated to a next level of …

This review investigates cutting-edge electroencephalography (EEG) signal processing
techniques, focusing on noise reduction, artifact removal, and feature extraction. The study …

Background The diagnosis of major depressive disorder (MDD) is commonly based on the
subjective evaluation by experienced psychiatrists using clinical scales. Hence, it is …