Practical Biomedical Signal Analysis Using MATLAB®  book cover
1st Edition

Practical Biomedical Signal Analysis Using MATLAB®

ISBN 9781439812020
Published September 12, 2011 by CRC Press
324 Pages 14 Color & 97 B/W Illustrations

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Book Description

Practical Biomedical Signal Analysis Using MATLAB® presents a coherent treatment of various signal processing methods and applications. The book not only covers the current techniques of biomedical signal processing, but it also offers guidance on which methods are appropriate for a given task and different types of data.

The first several chapters of the text describe signal analysis techniques—including the newest and most advanced methods—in an easy and accessible way. MATLAB routines are listed when available and freely available software is discussed where appropriate. The final chapter explores the application of the methods to a broad range of biomedical signals, highlighting problems encountered in practice.

A unified overview of the field, this book explains how to properly use signal processing techniques for biomedical applications and avoid misinterpretations and pitfalls. It helps readers to choose the appropriate method as well as design their own methods.

Table of Contents

Introductory Concepts
Stochastic and deterministic signals, concepts of stationarity and ergodicity
Discrete signals
Linear time invariant systems
Duality of time and frequency domain
Hypotheses testing
Surrogate data techniques

Single Channel (Univariate) Signal
Probabilistic models
Stationary signals
Non-stationary signals
Non-linear methods of signal analysis 

Multiple Channels (Multivariate) Signals
Cross-estimators: cross-correlation, cross-spectra, coherence (ordinary, partial, multiple)
Multivariate autoregressive model (MVAR)
Measures of directedness
Non-linear estimators of dependencies between signals
Comparison of the multichannel estimators of coupling between time series
Multivariate signal decompositions

Application to Biomedical Signals
Brain signals: local field potentials (LFP), electrocorticogram (ECoG), electroencephalogram (EEG), and magnetoencephalogram (MEG), event related responses (ERP), and evoked fields (EF)
Heart signals
Gastro-intestinal signals 
Acoustic signals



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K.J. Blinowska is a professor at University of Warsaw, where she was director of Graduate Studies in Biomedical Physics and head of the Department of Biomedical Physics. She has been at the forefront in the development of new advanced time-series methods for research and clinical applications.

J. Żygierewicz is an assistant professor at University of Warsaw. His research focuses on time-frequency analysis of EEG and MEG signals, statistical analysis of event-related synchronization and desynchronization in EEG and MEG, and realistic neuronal network models that provide insight into the mechanisms underlying the effects observed in EEG and MEG signals.