Practical Biomedical Signal Analysis Using MATLAB®

Katarzyna J. Blinowska, Jarosław Żygierewicz

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English

CRC Press
27 October 2021

Biomedical engineering; Medical physics; Communications engineering & telecommunications

Series: Series in Medical Physics and Biomedical Engineering

Covering the latest cutting-edge techniques in biomedical signal processing while presenting a coherent treatment of various signal processing methods and applications, this second edition of Practical Biomedical Signal Analysis Using MATLAB® also offers practical guidance on which procedures are appropriate for a given task and different types of data.

It begins by describing signal analysis techniques—including the newest and most advanced methods in the field—in an easy and accessible way, illustrating them with Live Script demos. MATLAB® routines are listed when available, and freely available software is discussed where appropriate. The book concludes by exploring the applications of the methods to a broad range of biomedical signals while highlighting common problems encountered in practice.

These chapters have been updated throughout and include new sections on multiple channel analysis and connectivity measures, phase-amplitude analysis, functional near-infrared spectroscopy, fMRI (BOLD) signals, wearable devices, multimodal signal analysis, and brain-computer interfaces.

By providing a unified overview of the field, this book explains how to integrate signal processing techniques in biomedical applications properly and explores how to avoid misinterpretations and pitfalls. It helps readers to choose the appropriate method as well as design their own methods. It will be an excellent guide for graduate students studying biomedical engineering and practicing researchers in the field of biomedical signal analysis.

Features:

Fully updated throughout with new achievements, technologies, and methods and is supported with over 40 original MATLAB Live Scripts illustrating the discussed techniques, suitable for self-learning or as a supplement to college courses

Provides a practical comparison of the advantages and disadvantages of different approaches in the context of various applications

Applies the methods to a variety of signals, including electric, magnetic, acoustic, and optical

Katarzyna J. Blinowska is a Professor emeritus at the University of Warsaw, Poland, where she was director of Graduate Studies in Biomedical Physics and head of the Department of Biomedical Physics. Currently, she is employed at the Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. She has been at the forefront in developing new advanced time-series methods for research and clinical applications.

Jarosław Żygierewicz is a Professor at the University of Warsaw, Poland. His research focuses on developing methods for analyzing EEG and MEG signals, brain-computer interfaces, and applications of machine learning in signal processing and classification.

By: Katarzyna J. Blinowska, Jarosław Żygierewicz
Imprint: CRC Press
Country of Publication: United Kingdom
Edition: 2nd edition
Dimensions: Height: 234mm, Width: 156mm,
Weight: 725g
ISBN: 9781138364417
ISBN 10: 113836441X
Series: Series in Medical Physics and Biomedical Engineering
Pages: 354
Publication Date: 27 October 2021
Audience: College/higher education , General/trade , Primary , ELT Advanced
Format: Hardback
Publisher's Status: Active

1. A Short Introduction to Matlab. 2. Introductory Concepts. 3. Single Channel (Univariate) Signal. 4. Multiple Channels (Multivariate) Signals 5. Application to Biomedical Signals.

K. J. Blinowska　is a Professor emeritus at the University of Warsaw, Poland, where she was director of Graduate Studies in Biomedical Physics and head of the Department of Biomedical Physics. Currently, she is employed at the Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. She has been at the forefront in developing new advanced time-series methods for research and clinical applications. J. Żygierewicz　is a Professor at the University of Warsaw, Poland. His research focuses on developing methods for analyzing EEG and MEG signals, brain-computer interfaces, applications of machine learning in signal processing and classification.