TY  - BOOK
AU  - Bronzino,Joseph D.
AU  - Liang,Hualou
AU  - Peterson,Donald R.
TI  - Biosignal processing: principles and practices 
SN  - 9781439871430 (hardcover : alk. paper)
AV  - RC386.6.B7 B56 2013
U1  - 612.8/2 L981b 23
PY  - 2013///
CY  - Boca Raton
PB  - CRC Press/Taylor & Francis, 
KW  - Brain Mapping
KW  - Brain Waves
KW  - physiology
KW  - Brain
KW  - Electrodiagnosis
KW  - methods
KW  - Nervous System Physiological Phenomena
KW  - Signal Processing, Computer-Assisted
N1  - Includes bibliographical references and index; 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; License restrictions may limit access
N2  - "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"--
UR  - http://www.columbia.edu/cgi-bin/cul/resolve?clio10112175.001
UR  - http://www.columbia.edu/cgi-bin/cul/resolve?clio10112175.002
ER  -