000 03552nam a2200349 a 4500
999 _c16803
001 17330057
003 BD-KhUET
005 20181108144309.0
008 181108s2013 flua b 001 0 eng
010 _a 2012022198
020 _a9781439871430 (hardcover : alk. paper)
035 _a(DNLM)101585381
040 _aDNLM/DLC
082 0 0 _a612.82
245 0 0 _aBiosignal processing :
_bprinciples and practices /
_cedited by Hualou Liang, Joseph D. Bronzino, and Donald R. Peterson.
260 _aBoca Raton :
_bCRC Press/Taylor & Francis,
300 _a1 volume (various pagings) :
_billustrations (some color) ;
_c26 cm
504 _aIncludes bibliographical references and index.
505 0 _aCausality 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 _a"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"--
650 1 2 _aBrain Mapping.
650 2 2 _aBrain
650 2 2 _aBrain Waves
650 2 2 _aElectrodiagnosis
650 2 2 _aNervous System Physiological Phenomena.
650 2 2 _aSignal Processing, Computer-Assisted.
700 1 _aLiang, Hualou
700 1 _aBronzino, Joseph D.,
700 1 _aPeterson, Donald R.
942 _2ddc