Quantitative Eeg Analysis, Breakthrough Official Reports Deny

Some kinds of quantification are always involved in signals EEG analysis, even in visual inspection. As digital computer technology developed large amounts of data manipulated and new concepts as pattern recognition and event-related desyncronization/synchronization arrived, “eyeballing” EEG interpretation became inappropriate. The problems rose to widespread acceptance and use of QEEG methods for clinical purposes (different filters cutoffs, lack of reproducibility between various software and hardware platforms etc.) are not fundamentals but solvable issues. It rather is the dogmatic reports, such that of American Academy of Neurology and the American Clinical Neurophysiology Society (1987, 1997) was responsible for that. Because of simplicity and noninvasive character of collection data, EEG remains a powerful tool in clinician hands, yet with a vast unexplored territory. Data mining analysis must provide a clear way to clinical diagnosis, and here demanding efforts are required. Our aim is directed to pattern recognition methods and neural network models in order to specific characterize diseases quite different like Alzheimer, epilepsy or Parkinson disease.