3rd International Conference on Bioinformatics and Computational Biology

Invited Keynote Speakers

Hojjat Adeli Hojjat Adeli, Ph.D.
Professor, Department of Biomedical Informatics
Dept. of Neuroscience
Center for Biomedical Engineering
Director, Knowledge Engineering Lab
The Ohio State University

Automated Signal Processing of Brain Waves for Diadnosis of Neurological Disorfers

Novel wavelet-chaos-neural network models are presented for signal processing of brain waves as recorded by electroencephalographs (EEGs) for automated EEG-based diagnosis of neurological disorders. Through extensive parametric studies and information reuse and integration certain combinations of parameters from the EEG sub-bands were discovered to be effective markers for seizure detection and epilepsy diagnosis. The model can distinguish among healthy, interictal, and ictal EEGs with a high accuracy of more than 96% substantially better than practicing neurologists and epileptologists. The extension of the methodology for automated diagnosis of Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), and early onset diagnosis of the Alzheimer 's Disease (AD) are also discussed briefly.

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