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