Biosignal Processing PrinciPles Practices and Biosignal Processing PrinciPles Practices and edited by Hualou liang Joseph d. Bronzino donald r. Peterson Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Group, an informa business First published 2013 by CRC Press Published 2019 by CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2013 by Taylor & Francis Group, LLC CRC Press is an imprint of the Taylor & Francis Group, an informa business No claim to original U.S. Government works Version Date: 20120608 ISBN-13: 978-1-4398-7143-0 (hbk) This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. 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CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identifica- tion and explanation without intent to infringe. Library of Congress Cataloging‑in‑Publication Data Biosignal processing : principles and practices / edited by Hualou Liang, Joseph D. Bronzino, and Donald R. Peterson. p. ; cm. Includes bibliographical references and index. ISBN 978-1-4398-7143-0 (hardcover : alk. paper) I. Liang, Hualou II. Bronzino, Joseph D., 1937- III. Peterson, Donald R. [DNLM: 1. Brain Mapping. 2. Brain--physiology. 3. Brain Waves--physiology. 4. Electrodiagnosis--methods. 5. Nervous System Physiological Phenomena. 6. Signal Processing, Computer-Assisted. WL 335] 612.8’2--dc23 2012022198 Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com Contents Preface ............................................................................................................................................vii Editors .............................................................................................................................................ix Contributors ..................................................................................................................................xi 1 Digital Biomedical Signal Acquisition and Processing ......................................1-1 Luca T. Mainardi, Anna M. Bianchi, and Sergio Cerutti 2 Time–Frequency Signal Representations for Biomedical Signals ....................2-1 G. Faye Boudreaux-Bartels and Robin Murray 3 Multivariate Spectral Analysis of Electroencephalogram: Power, Coherence, and Second-Order Blind Identification ..............................3-1 Ramesh Srinivasan and Siyi Deng 4 General Linear Modeling of Magnetoencephalography Data ...........................4-1 Dimitrios Pantazis, Juan Luis Poletti Soto, and Richard M. Leahy 5 Emergence of Groupwise Registration in MR Brain Study ...............................5-1 Guorong Wu, Hongjun Jia, Qian Wang, Feng Shi, Pew-Thian Yap, and Dinggang Shen 6 Functional Optical Brain Imaging ...........................................................................6-1 Meltem Izzetoglu 7 Causality Analysis of Multivariate Neural Data ...........................................7-1 Maciej Kamin´ski and Hualou Liang Index ...........................................................................................................................................................Index-1 v Preface Biosignal processing has been around for decades, but it still seems to be growing in popularity. With the rise of advanced computerized data collection systems, monitoring devices, and instrumentation technologies, large and complex datasets simply accrue as an inevitable part of biomedical enterprise. The availability of large quantities of biomedical data not only offers unprecedented opportunities to advance our understanding of the underlying biological and physiologic functions, structures, and dynamics but also drives tremendous progress toward innovative methods in biosignal processing. As such, this field has advanced to a conspicuous stage that biosignal processing has become an integral part in all phases of biomedical research and development. The purpose of this book is to provide state-of-the-art coverage of contemporary methods in biosignal processing with an emphasis on brain signal analysis. The first two chapters in this book present fundamental aspects of biomedical signal processing, which should be accessible to the general audi- ence. Chapter 1 provides a general overview of basic concepts in biomedical signal acquisition and processing, whereas Chapter 2 deals with the nonstationary and transient nature of signals by intro- ducing time− frequency analysis and discusses its applications to signal analysis and detection prob- lems in bioengineering. The next four chapters address emerging methods for brain signal processing, each focusing on spe- cific noninvasive imaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), magnetic resonance imaging (MRI), and functional near-infrared spectroscopy (fNIR). Chapter 3 covers a multivariate spectral analysis of EEG data using power, coherence, and second-order blind identification. Chapter 4 introduces a general linear modeling approach for the analysis of induced and evoked responses in MEG. Chapter 5 presents the progress in groupwise registration algorithms for effective MRI medical image analysis. Chapter 6 describes the basis of optical imaging, fNIR instru- mentation, and signal analysis in various cognitive studies. Chapter 7 reviews recent advances of causal influence measures such as the Granger causality for analyz- ing multivariate neural data. For basic applications, the emphasis is on the typical analysis of spike trains, EEG, and fMRI BOLD data, each representing a major recording modality used in neuroscience research. For clinical applications, epileptogenic seizure localization is selected as a direct demonstration. The topics covered in this book reflect an ongoing evolution in biosignal processing. As biomedical datasets grow larger and more complicated, emerging signal processing methods that analyze and inter- pret these data have gained in importance. We hope that this book will aid the process for biosignal analysis and stimulate new ideas and opportunities for developing cutting-edge computational methods for biosignal processing, which will in turn accelerate laboratory discoveries into treatments for patients. All the contributors of this book share this vision and herein are gratefully recognized for donating their talent and time so that the promise of biosignal processing will be fulfilled. Hualou Liang Philadelphia, Pennsylvania vii Editors Hualou Liang is a professor at Drexel University, School of Biomedical Engineering. Dr. Liang received his PhD in physics from the Chinese Academy of Sciences, Beijing, China. He studied signal processing at Dalian University of Technology, Dalian, China. Dr. Liang has been a postdoctoral researcher in Tel- Aviv University, Israel, Max Planck Institute for Biological Cybernetics, Germany, and the Center for Complex Systems and Brain Sciences, Florida Atlantic University, USA. Professor Liang focuses his research study on neuroengineering, neuroinformatics, functional brain imaging, cognitive and computational neuroscience, and biomedical signal processing. Dr. Liang’s team explores neural mechanisms of visual perception during various cognitive tasks using computational approaches. His recent work deals with (1) development of software package (www.brain-smart.org) for analyzing brain circuits, (2) neuronal oscillations and attentional control, (3) development of advanced signal processing methods for the analysis of nonstationary, multivariate neurobiological data (spikes, field potentials, EEG/MEG, fMRI, etc.), and (4) algorithm development for brain–computer interface or brain–machine interface. Joseph D. Bronzino earned a BSEE from Worcester Polytechnic Institute, Worcester, Massachusetts, in 1959, an MSEE from the Naval Postgraduate School, Monterey, California, in 1961, and a PhD in electri- cal engineering from Worcester Polytechnic Institute in 1968. He is presently the Vernon Roosa Professor of Applied Science, an endowed chair at Trinity College, Hartford, Connecticut, and president of the Biomedical Engineering Alliance and Consortium (BEACON), a nonprofit organization consist- ing of academic and medical institutions as well as corporations dedicated to the development and com- mercialization of new medical technologies (www.beaconalliance.org). Dr. Bronzino is the author of over 200 articles and 11 books, including Technology for Patient Care (C.V. Mosby, 1977), Computer Applications for Patient Care (Addison-Wesley, 1982), Biomedical Engineering: Basic Concepts and Instrumentation (PWS Publishing Co., 1986), Expert Systems: Basic Concepts (Research Foundation of State University of New York, 1989), Medical Technology and Society: An Interdisciplinary Perspective (MIT Press and McGraw-Hill, 1990), Management of Medical Technology (Butterworth/Heinemann, 1992), The Biomedical Engineering Handbook (CRC Press, 1st Ed., 1995; 2nd Ed., 2000; 3rd Ed., 2005 ), and Introduction to Biomedical Engineering (Academic Press 1st Ed., 1999; 2nd Ed., 2005), Dr. Bronzino is a fellow of IEEE and the American Institute of Medical and Biological Engineering (AIMBE), an honorary member of the Italian Society of Experimental Biology, past chairman of the Biomedical Engineering Division of the American Society for Engineering Education (ASEE), a charter member and former vice president of the Connecticut Academy of Science and Engineering (CASE), and a charter member of the American College of Clinical Engineering (ACCE), the Association for the Advancement of Medical Instrumentation (AAMI), past president of the IEEE-Engineering in Medicine and Biology Society (EMBS), past chairman of the IEEE Health Care Engineering Policy Committee ix