Computational Intelligence Techniques in Diagnosis of Brain Diseases

This book highlights a new biomedical signal processing method of extracting a specific underlying signal from possibly noisy multi-channel recordings, and shows that the method is suitable for extracting independent components from the measured electroen

  • PDF / 2,358,989 Bytes
  • 81 Pages / 439.37 x 666.142 pts Page_size
  • 79 Downloads / 183 Views

DOWNLOAD

REPORT


Sasikumar Gurumoorthy Naresh Babu Muppalaneni Xiao-Zhi Gao

Computational Intelligence Techniques in Diagnosis of Brain Diseases

SpringerBriefs in Applied Sciences and Technology Forensic and Medical Bioinformatics

Series editors Amit Kumar, Hyderabad, India Allam Appa Rao, Hyderabad, India

More information about this series at http://www.springer.com/series/11910

Sasikumar Gurumoorthy Naresh Babu Muppalaneni Xiao-Zhi Gao

Computational Intelligence Techniques in Diagnosis of Brain Diseases

123

Sasikumar Gurumoorthy Department of Computer Science and Systems Engineering Sree Vidyanikethan Engineering College Tirupati India

Xiao-Zhi Gao Machine Vision and Pattern Recognition Laboratory Lappeenranta University of Technology Lappeenranta Finland

Naresh Babu Muppalaneni Department of Computer Science and Systems Engineering Sree Vidyanikethan Engineering College Tirupati India

ISSN 2191-530X ISSN 2191-5318 (electronic) SpringerBriefs in Applied Sciences and Technology ISSN 2196-8845 ISSN 2196-8853 (electronic) SpringerBriefs in Forensic and Medical Bioinformatics ISBN 978-981-10-6528-6 ISBN 978-981-10-6529-3 (eBook) DOI 10.1007/978-981-10-6529-3 Library of Congress Control Number: 2017952914 © The Author(s) 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Contents

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Brain Signals Processing (EEG) . . . . . . . . . . . . . . . . . . . . . . . 1.2 Research Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 The Necessity for Automated Classification . . . . . . . . . . . . . . 1.4 EEG Arti