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LEADER 00000cam a2200325 a 4500
001 u41105
003 SIRSI
008 160815s2013 xxua b 001 0 eng d
020 9781439871430 (hardcover : alk. paper)
050 00 RC386.6.B7 |bB56 2013
245 00 Biosignal processing : |bprinciples and practices /
|cedited by Hualou Liang, Joseph D. Bronzino, and Donald
R. Peterson.
260 Boca Raton : |bCRC Press/Taylor & Francis, |c2013
300 1 volume (various paging) : |billustrations (some color) ;
|c26 cm.
504 Includes bibliographical references and index.
505 Causality analysis of multivariate neural data / Maciej
Kaminski, Hualou Liang -- Multivariate spectral analysis
of EEG : power, coherence, and second-order blind
identification / Ramesh Srinivasan and Siyi Deng --
Functional optical brain imaging / Meltem Izzetoglu --
General linear modeling of magnetoencephalography data /
Dimitrios Pantazis, Juan Luis Poletti Soto, Richard M.
Leahy -- Emergence of groupwise registration in MR brain
study / Guorong Wu ... [et al.] -- Digital biomedical
signal acquisition and processing / Luca Mainardi, Sergio
Cerutti -- Time-frequency signal representations for
biomedical signals / G. Faye Boudreaux-Bartels and Robin
Murray.
520 "This book provides state-of-the-art coverage of
contemporary methods in biosignal processing, with
emphasis on brain signal analysis. The topics covered in
this book reflect an ongoing evolution in biosignal
processing. As biomedical data sets grow larger and more
complicated, emerging signal processing methods to analyze
and interpret these data have gained in importance. This
book discusses the process for biosignal analysis and
stimulates new ideas and opportunities for developing
cutting-edge computational methods for biosignal
processing, which will in turn accelerate laboratory
discoveries into treatments for patients. Provides a
general overview of basic concepts in biomedical signal
acquisition and processing. Discusses nonstationary and
transient nature of signals by introducing time-frequency
analysis and its applications to signal analysis and
detection problems in bioengineering. Covers emerging
methods for brain signal processing, each focusing on
specific non-invasive imaging techniques such as
electroencephalography (EEG), magnetoencephalography (MEG),
magnetic resonance imaging (MRI) and functional near-
infrared spectroscopy (fNIR). Explores a multivariate
spectral analysis of EEG data using power, coherence and
second-order blind identification. Introduces a general
linear modeling approach for the analysis of induced and
evoked response in MEG. Presents the progress in groupwise
registration algorithms for effective MRI medical image
analysis. Examines the basis of optical imaging, fNIR
instrumentation and signal analysis in various cognitive
studies. Reviews recent advances of causal influence
measures such as Granger causality for analyzing
multivariate neural data"-- / Provided by publisher
700 1 Liang, Hualou
700 1 Bronzino, Joseph D.,|d1937-
700 1 Peterson, Donald R