Automated EEG-based diagnosis of the neurological and psychiatric disorders

In this keynote lecture the author presents a research ideology, a novel multi-paradigm methodology, and advanced computational models for automated electroencephalogram (EEG)-based diagnosis of neurological and psychiatric disorders. The methodology is based on integration of three different computing technologies and problem solving paradigms: neural networks, wavelets, and the chaos theory. Examples of the research performed by the authors and his associates for automated diagnosis of epilepsy, the Alzheimer´s Disease, Attention Deficit Hyperactivity Disorder (ADHD), and Autism Spectrum Disorder (ASD) are discussed.