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BL
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| Record Number
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889755
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| Title & Author
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Computational EEG analysis : : methods and applications /\ Chang-Hwan Im, editor.
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| Publication Statement
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Singapore :: Springer,, 2018.
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| Series Statement
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Biological and medical physics, Biomedical engineering,
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| Page. NO
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1 online resource
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| ISBN
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9789811309083
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: 9789811309090
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: 9811309086
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: 9811309094
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9789811309076
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9811309078
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| Contents
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Intro; Preface; Contents; Contributors; Abbreviations; Introduction; 1 Basics of EEG: Generation, Acquisition, and Applications of EEG; 1.1 Generation of EEG; 1.2 Acquisition of EEG; 1.3 Computational EEG Analysis; 1.3.1 EEG Spectral Analysis; 1.3.2 Event-Related Potential Analysis; 1.3.3 EEG Source Imaging; 1.3.4 Functional Connectivity Analysis; 1.4 Applications of EEG; References; Methods; 2 Preprocessing of EEG; 2.1 Introduction; 2.2 Early-Stage Preprocessing; 2.2.1 Characteristics of Background EEG; 2.2.2 Line Noise Removal; 2.2.3 Referencing; 2.2.4 Bad Channel Detection.
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2.3 Artifact Removal2.3.1 Sources of Artifacts; 2.3.2 Artifact Removal Methods; 2.4 Discussion; References; 3 EEG Spectral Analysis; 3.1 Introduction; 3.2 Methodological Background; 3.2.1 Continuous Fourier Transform; 3.2.2 Discrete Fourier Transform; 3.2.3 Fast Fourier Transform; 3.2.4 Aliasing and Leakage; 3.2.5 Short-Time Fourier Transform; 3.3 Practical Remarks on EEG Spectral Analysis; 3.3.1 Choosing Adequate Sampling Frequency; 3.3.2 Analysis Window Size and Frequency Resolution; 3.3.3 Reducing Leakage; 3.3.4 Window Function for STFT; 3.3.5 Absolute Power Versus Relative Power.
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3.3.6 Other Considerations in Spectral AnalysisReferences; 4 The Analysis of Event-Related Potentials; 4.1 Introduction; 4.2 General Considerations in ERP Analysis; 4.3 Time Domain Analysis; 4.3.1 The Additive Generative Model; 4.3.2 Ensemble Average Estimations; 4.3.3 Multivariate Filtering Methods; 4.3.4 Principal Component Analysis; 4.3.5 The Common Pattern; 4.3.6 Blind Source Separation; 4.4 Time-Frequency Domain Analysis; 4.5 Spatial Domain Analysis; 4.6 Inferential Statistics; 4.7 Single-Sweep Classification; References; 5 EEG Source Imaging and Multimodal Neuroimaging.
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5.1 From the Brain to the Scalp-The Forward Problem5.1.1 Volume Source and the Poisson's Equation; 5.1.2 The Current Dipole; 5.1.3 The Forward Problem-Algebra; 5.1.4 The Volume Conductor: Type of Models; 5.1.5 A Note on Tissue Conductivity Values; 5.2 From the Scalp to the Brain-The Inverse Problem; 5.2.1 Parametric Optimization Methods; 5.2.2 Non-parametric Optimization Methods; 5.3 Multimodal Integration; 5.3.1 MEG and EEG Combinations; 5.3.2 FMRI and EEG-FMRI Combinations; 5.3.3 EEG-FNIRS; 5.4 Conclusion; References; 6 Methods for Functional Connectivity Analysis; 6.1 Introduction.
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6.2 Procedure for the FCA6.3 FC Metrics; 6.3.1 Cross-Correlation Function (CCF); 6.3.2 Coherence; 6.3.3 Phase Locking Value (PLV); 6.3.4 Phase Lag Index (PLI); 6.3.5 Mutual Information (MI); 6.3.6 Granger Causality (GC); 6.3.7 Partial Directed Coherence (PDC); 6.4 Volume Conduction Problem; 6.4.1 FCA Between the Signals from Surface Electrodes; 6.4.2 Spatial Filtering; 6.4.3 FC Measures Robust to Volume Conduction Effect; 6.5 EEG FC Analysis on Source Space; 6.6 Determination of Significance; 6.7 Conclusions; References; Applications.
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| Abstract
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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.
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| Subject
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Electroencephalography.
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Electroencephalography.
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HEALTH FITNESS-- Diseases-- General.
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MEDICAL-- Clinical Medicine.
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MEDICAL-- Diseases.
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MEDICAL-- Evidence-Based Medicine.
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MEDICAL-- Internal Medicine.
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| Dewey Classification
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616.8/047547
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| LC Classification
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RC386.6.E43
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| Added Entry
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Im, Chang-Hwan
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