Details

Title Computational EEG Analysis : Methods and Applications
Author Chang-Hwan Im (Editor)
Binding Hardback
Condition New
Pages 228
Volumes 1
Language ENG
Publisher Springer
Publication date 2018-08-28
Illustrated Yes
Features Illustrated
Bookseller's Inventory # ria9789811309076_inp
ISBN 9789811309076 / 9811309078
Weight 1.14 lbs (0.52 kg)
Dimensions 9.21 x 6.14 x 0.56 in (23.39 x 15.60 x 1.42 cm)
Category Science
Dewey Decimal Code 004
Quantity available 131

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From the publisher

This book introduces and reviews all of the currently available methods being used for computational electroencephalogram (EEG) analysis, from the fundamentals through to the state-of-the-art. The aim of the book is to help biomedical engineers and medical doctors who use EEG to better understand the methods and applications of computational EEG analysis from a single, well-organized resource.

Following a brief introduction to the principles of EEG and acquisition techniques, the book is divided into two main sections. The first of these covers analysis methods, beginning with preprocessing, and then describing EEG spectral analysis, event-related potential analysis, source imaging and multimodal neuroimaging, and functional connectivity analysis. The following section covers application of EEG analysis to specific fields, including the diagnosis of psychiatric diseases and neurological disorders, brain-computer interfacing, and social neuroscience.

Aimed at practicing medical specialists, engineers, researchers and advanced students, the book features contributions from world-renowned biomedical engineers working across a broad spectrum of computational EEG analysis techniques and EEG applications.

From the rear cover

This book introduces and reviews all of the currently available methods being used for computational electroencephalogram (EEG) analysis, from the fundamentals through to the state-of-the-art. The aim of the book is to help biomedical engineers and medical doctors who use EEG to better understand the methods and applications of computational EEG analysis from a single, well-organized resource.

Following a brief introduction to the principles of EEG and acquisition techniques, the book is divided into two main sections. The first of these covers analysis methods, beginning with preprocessing, and then describing EEG spectral analysis, event-related potential analysis, source imaging and multimodal neuroimaging, and functional connectivity analysis. The following section covers application of EEG analysis to specific fields, including the diagnosis of psychiatric diseases and neurological disorders, brain-computer interfacing, and social neuroscience.

Aimed at practicing medical specialists, engineers, researchers and advanced students, the book features contributions from world-renowned biomedical engineers working across a broad spectrum of computational EEG analysis techniques and EEG applications.

About the author

Prof. Chang-Hwan Im graduated from the School of Electrical Engineering of Seoul National University, Korea, in 1999. He received his MS and PhD from the same university in 2001 and 2005, respectively. He worked as a Post-doctor in the Department of Biomedical Engineering at the University of Minnesota, MN, USA, from 2005 to 2006. From 2006 to 2011, he worked for the Department of Biomedical Engineering at Yonsei University, Korea, as an Assistant/Associate Professor. Since 2011, he has been working for the Department of Biomedical Engineering at Hanyang University, Korea, as a Professor. His research interests cover various fields of computational neuroengineering, especially brain-computer interfaces, the diagnosis of neuropsychiatric diseases, noninvasive brain stimulation, bioelectromagnetic source imaging, neuromarketing, and dynamic neuroimaging. He has authored more than 150 articles in peer-reviewed international journals. He is currently a Director of the Computational Neuroengineering Laboratory of Hanyang University, and he is Associate Editors of Biomedical Engineering Letters, Experimental Neurobiology, and Brain-Computer Interfaces.

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