Automated EEG-Based Diagnosis of Neurological Disorders Inventing the Future of Neurology
Auteurs : Adeli Hojjat, Ghosh-Dastidar Samanwoy
Based on the authors? groundbreaking research, Automated EEG-Based Diagnosis of Neurological Disorders: Inventing the Future of Neurology presents a research ideology, a novel multi-paradigm methodology, and advanced computational models for the automated EEG-based diagnosis of neurological disorders. It is based on the ingenious integration of three different computing technologies and problem-solving paradigms: neural networks, wavelets, and chaos theory. The book also includes three introductory chapters that familiarize readers with these three distinct paradigms.
After extensive research and the discovery of relevant mathematical markers, the authors present a methodology for epilepsy diagnosis and seizure detection that offers an exceptional accuracy rate of 96 percent. They examine technology that has the potential to impact and transform neurology practice in a significant way. They also include some preliminary results towards EEG-based diagnosis of Alzheimer?s disease.
The methodology presented in the book is especially versatile and can be adapted and applied for the diagnosis of other brain disorders. The senior author is currently extending the new technology to diagnosis of ADHD and autism. A second contribution made by the book is its presentation and advancement of Spiking Neural Networks as the seminal foundation of a more realistic and plausible third generation neural network.
Introduction and Basic Concepts. Automated EEG-Based Diagnosis of Epilepsy. Automated EEG-Based Diagnosis of the Alzheimer's Disease. The Next Generation of Neural Networks: Spiking Neural Networks.
Hojjat Adeli is the Abba G. Lichtenstein Professor at The Ohio State University, Editor-in-Chief of the International Journal of Neural Systems, and author of 14 pioneering books. Samanwoy Ghosh-Dastidar is Principal Biomedical Engineer at ANSAR Medical Technologies in Philadelphia. Nahid Dadmehr is a board-certified neurologist in practice in Ohio since 1991.
Date de parution : 06-2017
15.6x23.4 cm
Date de parution : 02-2010
Ouvrage de 400 p.
15.6x23.4 cm
Thèmes d’Automated EEG-Based Diagnosis of Neurological Disorders :
Mots-clés :
Seizure Detection; EEG Classification; seizure; Spike Time; detection; Output Spike; wavelet; Classification Accuracy; transform; Wavelet Analysis; neural; Wavelet Transform; network; Training Size; radial; EEG Study; basis; Spike Trains; function; Ictal EEG; networks; EEG Signal; Radial Basis Function Neural Network; Interictal EEG; Normal EEG; Epilepsy Diagnosis; Synaptic Weights; Feature Space; Postsynaptic Neuron; Embedding Dimension; Hidden Layer; EEG Slow; Chaos Analysis; XOR Problem; Presynaptic Neuron