Ebook: Practical Biomedical Signal Analysis Using MATLAB®

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 channels analysis and connectivity measures, phase-amplitude analysis, functional Near Infrared Spectroscopy, fMRI (BOLD) signals, wearable devices, multimodal signal analysis and the Brain Computer Interface.

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

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.