脑电信号的介绍，分类。信号处理的基本方法。脑电信号的分析处理以及应用EEG SIGNALPROCESSINGEEG SIGNALPROCESSINGSaeid Sanei and J.A. ChambersCentre of Digital Signal ProcessingCardiff University, UKICENTENNIAL1807③WILE2。7BICENTENNIALJohn Wiley Sons, LtdCopyright o 2007John wiley sons Ltd, The Atrium, Southern gate, ChichesterWest Sussex Po19 8SQ, EnglandTelephone(+44)1243779777Email (for orders and customer service enquiries ): cS-books @wiley. co ukVisitourhoMePageonwww.wileyeurope.comorwww.wiley.comAll Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system or transmittedany form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except underthe terms of the Copyright, Designs and Patents Act 1988 or under the terms of a licence issued by theCopyright Licensing Agency Ltd, 90 Tottenham Court Road, London WIT 4LP, UK, without the permission inwriting of the Publisher. 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Ifprofessional advice or other expert assistance is required, the services of a competent professional should besoughtOther Wiley Editorial officesJohn Wiley sons Inc, lll River Street, Hoboken, NJ 07030, USAJossey-Bass, 989 Market Street, San Francisco, Ca 94103-1741, USAWiley-VCH Verlag GmbH, Boschstr. 12, D-69469 Weinheim, GermanyJohn wiley sons australia ltd 42 McDougall Street. Milton. Queensland 4064. australiaJohn Wiley sons(Asia) Pte Ltd, 2 Clementi Loop #02-01, Jin Xing Distripark, Singapore 129809John Wiley sons Canada Ltd, 6045 Freemont Blvd, Mississauga, Ontario, L5R 4J3, CanadaWiley also publishes its books in a variety of electronic formats. Some content that appearsin print may not be available in electronic booksAnniversary Logo Design: Richard J PacificoLibrary of Congress Cataloging-in-Publication DataSanei. saeidEEG signal processing/Saeid Sanei and Jonathon ChambersIncludes bibliographical referencesISBN978-0-470-02581-9(alk. paper)1. Electroencephalography. 2. Signal processing. I. Chambers, Jonathon IITitleIDNLM: 1. Electroencephalography -methods. 2. Evoked Potentials. 3. SignalProcessing, Computer-Assisted. WL 150 S223e 20071RC3866E43S25220076168047547-dc222007019900British Library Cataloguing in Publication DataA catalogue record for this book is available from the British LibraryISBN-13978-0-470-02581-9Typeset in 10/12 Times by Laserwords Private Limited, Chennai, IndiaPrinted and bound in Great Britain by Antony Rowe Ltd, Chippenham, WiltshireThis book is printed on acid-free paper responsibly manufactured from sustainable forestryin which at least two trees are planted for each one used for paper productionContentsPrefaceList of abbreviationsList of Symbols1 Introduction to EEG1.1 History1. 2 Neural activities1.3 Action potential1. 4 EEG Generation1.5 Brain rhythms101.6 EEG Recording and Measurement131.6.1 Conventional Electrode positioning151.6.2 Conditioning the signals181. 7 Abnormal eeg patterns201.8 Ageing1.9 Mental Disorders1.9. Dementia221.9.2 Epileptic seizure and Nonepileptic attacks1.9.3 Psychiatric Disorders1.9.4 External et∫ects1.10 Summary and conclusions30References2 Fundamentals of EEG Signal Processing352.1 EEG Signal modelling362. Linear models422.1.2 Nonlinear Modelling2.1.3 Generating EEG Signals Based on Modelling the Neuronal activities2.2 Nonlinearity of the medium502.3 Nonstationarity2.4 Signal segmentation512.5 Signal Transforms and Joint Time-Frequency Analysis2.5./ Wavelet Transform582.5.2 Ambiguity Function and the Wigner-Ville distributionContents2.6 Coherency, Multivariate Autoregressive(MVAR) Modelling, and Directed TransferFunction TF)672.7 Chaos and dynamical analysis712.7.1 Entropy712.7.2 Kolmogorov Entropy712.7.3 Lyapunov Exponents2.7.4 Plotting the Attractor Dimensions from the Time serie742.7.5 Estimation of lyapunov Exponents from the Time series752.7.6 Approximate Entropy772.7.7 Using the Prediction Order782.8 Filtering and denoising2.9 Principal Component Analysis832.9.1 Singular-Value decomposition842.10 Independent Component analysis862.10. Instantaneous bss2.10.2 Convolutive bss2.10.3 Sparse Component analysis982.10. 4 Nonlinear bss2.10.5 Constrained bss1002. 11 Application of Constrained BSS: Example1022.12 Signal parameter estimation1042.13 Classification Algorithms1052.13.1 Support Vector Machines1062.13.2 The k-Means algorithm1142. 14 Matching Pursuits1172. 15 Summary and Conclusionsl18References1193 Event-Related potentials1273.1 Detection, Separation, Localization, and Classification of P300 Signals1313.1.1 Using ICA1323.1.2 Estimating Single brain Potential Components by Modelling erp Waveforms 1323.1.3 Source Tracking3.1.4 Localization of the erP1373.1.5 Time-Frequency Domain analysis1423.1.6 Adaptive Filtering Approach1453.1.7 Prony's Approach for Detection of P300 Signals1483.1.8 Adaptive Time-Frequency Methods1513.2 Brain activity Assessment Using erP1533.3 Application of P300 to BCI1543.4 Summary and Conclusions155References1564 Seizure Signal analysis1614.1 Seizure detection1664.1.1 Adult Seizure detection1664.1.2 Detection of Neonate Seizure1714.2 Chaotic Behaviour of EEg Sources1754.3 Predictability of Seizure from the EEGs176Contents4.4 Fusion of eeg-fmri Data for seizure prediction1894.5 Summary and Conclusions191References915 EEG Source localization5.1 Introduction1975.1.1 General Approaches to Source localization5.1.2 Dipole assumption1985.2 Overview of the Traditional Approaches2015.2.1 CA Method2015.2.2 MUSIC algorithm2015.2.3 LORETA Algorithm2045.2.4 FOCUSS Algorithm2065.2.5 Standardized LOrETA205.2.6 Other Weighted Minimum Norm Solutions2085.2.7 Evaluation indices2095.2.8 Joint ICA-LORETA Approach2105.2.9 Partially constrained bss Method2115.3 Determination of the Number of sources2135. 4 Summary and conclusions215References2156 Sleep EEG2196. 1 Stages of Sleep2206.1.1 NREM Sleep2206.1.2 REM Sleep2226.2 The Influence of Circadian rhythms2226.3 Sleep Deprivation2246.4 Psychological Effects2246.5 Detection and Monitoring of Brain Abnormalities During Sleep by EEG Analysis2256.5.1 Detection of the Rhythmic Waveforms and Spindles Incorporating Blind SourceSeparation2256.5.2 Application of Matching Pursuit2276.5.3 Detection of Normal Rhythms and Spindles using Higher Order Statistics6.5.4 Application of Neural Networks2316.5.5 Model-Based Analysis6.5.6 Hybrid Methods2346.6 Concluding remar235References235Brain-Computer Interfacing2397.1 State of the art in bci2407. erd and Ers2437.1.2 Transient Beta Activity after the Movement7.1. 3 Gamma Band oscillations457.1.4 Long Delta Activity2457.2 Major Problems in bCI2457.2.1 Preprocessing of the eegs245EEG Signal processing7.3 Multidimensional eeg decomposition24873. Space-Time-Frequency method2517.3.2 Parallel Factor Analysis2517.4 Detection and Separation of ERP Signals7.5 Source Localization and Tracking of the moving sources within the brain7.6 Multivariant Autoregressive(MVAR) Modelling and Coherency Maps2557.7 Estimation of Cortical Connectivity2577.8 Summary and conclusionsReferences261Index267