R. Rangayyan – Biomedical Signal Analysis (Second edition, 2015)

Автор: R. Rangayyan
Название книги: Biomedical Signal Analysis (Second edition)
Формат: PDF
Жанр: Медицина
Страницы: 717
Качество: Изначально компьютерное, E-book

The book will help assist a reader in the development of techniques for analysis of biomedical signals and computer aided diagnoses with a pedagogical examination of basic and advanced topics accompanied by over 350 figures and illustrations.

Wide range of filtering techniques presented to address various applications
800 mathematical expressions and equations
Practical questions, problems and laboratory exercises
Includes fractals and chaos theory with biomedical applications

The first edition of this book has been received very well around the world. Professors
at several universities across North America, Europe, Asia, and other regions of
the world are using the book as a textbook. A low-cost paperback edition for selected
regions of the world and a Russian edition have been published. I have received several
messages and comments from many students, professors, and researchers via
mail and at conferences with positive feedback about the book. I am grateful to
IEEE andWiley for publishing and promoting the book and to the many users of the
book for their support and feedback.
I have myself used the book to teach my course ENEL 563 Biomedical Signal
Analysis at the University of Calgary. In addition to positive responses, I have received
suggestions from students and professors on revising the book to provide
additional examples and including advanced topics and discussions on recent developments
in the book. I also made notes identifying parts of the book that could be
improved for clarity, augmented with details for improved comprehension, and expanded
with additional examples for better illustrations of application. I have also
identified a few new developments, novel applications, and advanced techniques for
inclusion in the second edition to make the book more interesting and appealing to a
wider readership.

New Material in the Second Edition
In view of the success of the first edition, I have not made any major change in the
organization and style of the book. Notwithstanding a tighter format to reduce white
space and control the total number of pages, the second edition of the book remains
similar to the first edition in terms of organization and style of presentation. New
material has been inserted into the same chapters as before, thereby expanding the
book. The new topics have been chosenwith care not only to fit with the structure and
organization of the book but also to provide additional supportmaterial and advanced
topics that can be assimilated and appreciated in a first course or an advanced study
of the subject area.
Some of the substantial and important additions made to the book deal with the
following topics:
analysis of the variation of parameters of the electromyogram with force;
illustrations of the electroencephalogram with application to sleep analysis and
prediction of epileptic seizures;
details on the theory of linear systems and numerical examples related to convolution;
details on the z-transform and the Fourier transform along with additional examples
of Fourier spectra and spectral analysis of biomedical signals;
details on linear filters and their characteristics, such as the impulse response,
transfer function, and pole–zero diagrams;
description and demonstration of nonlinear order-statistic filters;
derivation of the matched filter;
derivations related to the complex cepstrum;
details on random processes and their properties;
wavelets and the wavelet transform with biomedical applications;
fractal analysis with biomedical applications;
time-frequency distributions and analysis of nonstationary signals with biomedical
applications;
principal component analysis, independent component analysis, and blind source
separation with biomedical applications;
monitoring of sleep apnea;
analysis of various types of bioacoustic signals that could bear diagnostic information;
and
methods for pattern analysis and classification with illustrations of application
to biomedical signals.
Discussions related to the topics listed above are spread throughout the book with
several new references added to assist the reader in further studies. Many more
problems and projects have been added at the ends of the chapters.
The first edition of the book (2002) has 516 pages (plus xxxv pages of front matter)
with nine chapters, 538 numbered equations (with many more equations not
numbered but as parts of procedures), 232 numbered figures (many with multiple
subfigures), and 265 references. The second edition (2015) has 672 pages (plus xliii
pages of frontmatter) in a more compact layout than the first edition, with nine chapters,
814 numbered equations (and many more equations not numbered but as parts
of procedures), 370 numbered figures (many with multiple subfigures), and 505 references.
The discussions on some of the new topics added were kept brief in order
to control the size of the book; regardless, the second edition is approximately 50%
larger than the first edition in several aspects.
Intended Audience
As with the first edition, the second edition is directed at engineering students in
their final (senior) year of undergraduate studies or in the first year of their graduate
studies. Electrical Engineering students with a good background in signals and
systems will be well prepared for the material in the book. Students in other engineering
disciplines, or in computer science, physics, mathematics, or geosciences,
should also be able to appreciate the material in the book. A course on digital signal
processing or digital filters would form a useful link to the material in the present
book, but a capable student without this background should be able to gain a basic
understanding of the subject matter. The introductory materials on systems, filters,
and transforms added in the second edition should assist the reader without formal
training on the same topics. Practicing engineers, computer scientists, information
technologists, medical physicists, and data-processing specialists working in diverse
areas such as telecommunications, seismic and geophysical applications, biomedical
applications, and hospital information systems may find the book useful in their
quest to learn advanced techniques for signal analysis. They could draw inspiration
from other applications of signal processing or analysis, and satisfy their curiosity
regarding computer applications in medicine and computer-aidedmedical diagnosis.
Teaching and Learning Plan
The book starts with an illustrated introduction to biomedical signals in Chapter 1.
Chapter 2 continues the introduction, with emphasis on the analysis of multiple channels
of correlated signals.
Chapter 3 deals exclusively with filtering of signals for removal of artifacts as an
important step before signal analysis. The basic properties of systems and transforms
as well as signal processing techniques are reviewed and described where required.
The chapter is written as a mix of theory and application so as to facilitate easy
comprehension of the basics of signals, systems, and transforms [1–4]. The emphasis
is on the application of filters to particular problems in biomedical signal analysis.
A large number of illustrations are included to provide a visual impression of the
problem and the effectiveness of the various filtering methods described.
Chapter 4 presents techniques that are particularly useful in the detection of events
in biomedical signals. Analysis of waveshape and waveform complexity of events
and components of signals is the focus of Chapter 5. Techniques for frequencydomain
characterization of biomedical signals and systems are presented in Chapter
6. A number of diverse examples are provided in all of the chapters. Attention is
directed to the characteristics of the problems that are encountered when analyzing
and interpreting biomedical signals, rather than to any specific diagnostic application
with particular signals.
The material in the book up to and including Chapter 6 provides more than adequate
material for a one-semester (13-week) course at the senior (fourth-year) engineering
level. My own teaching experience indicates that this material will require
about 38 hours of lectures. It would be desirable to augment the lectures with about
12 hours of tutorials (problem-solving sessions) and 10 laboratory sessions.
Modeling biomedical signal-generating processes and systems for parametric representation
and analysis is the subject of Chapter 7. Chapter 8 deals with the analysis
of nonstationary and multicomponent signals. The topics in these chapters are
of higher mathematical complexity than suitable for undergraduate courses. Some
sections may be selected and included in a first course on biomedical signal analysis
if there is particular interest in these topics. Otherwise, the two chapters could be left
for self-study by those in need of the techniques, or included in an advanced course.
Chapter 9 presents the final aspect of biomedical signal analysis, and provides an
introduction to pattern classification and diagnostic decision making. Although this
topic is advanced in nature and could form a graduate-level course on its own, the
material is introduced so as to draw the entire exercise of biomedical signal analysis
to its concluding stage of diagnostic decision. It is recommended that a few sections
from this chapter be included even in a first course on biomedical signal analysis so
as to give the students a flavor of the end result.
The topic of data compression has been deliberately left out of the book. Advanced
topics such as time-frequency distributions, wavelet-based analysis, independent
component analysis, and fractal analysis have been introduced briefly in the
second edition, but require further detailed study for completeness. Adaptive filters
and nonstationary signal analysis techniques are introduced in the book, but deserve
more attention, depth, and breadth. The references provided should assist the interested
reader in obtaining further advanced material.
Each chapter includes a number of study questions and problems to facilitate
preparation for tests and examinations. A number of laboratory exercises are also
provided at the end of each chapter, which could be used to formulate hands-on exercises
with real-life signals. Data files related to the problems and exercises at the
end of each chapter are available at the site
MATLABr programs to read the data are also provided in some cases.
It is strongly recommended that the first one or two laboratory sessions in the
course include visits to a local hospital, health sciences center, or clinical laboratory
to view and experience procedures related to biomedical signal acquisition and
analysis in a practical (clinical) setting. Signals acquired from fellow students and
professors could form interesting and motivating material for laboratory exercises,
and may be used to supplement the data files provided. A few workshops by physiologists,
neuroscientists, and cardiologists should also be included in the course so
as to provide the students with a nonengineering perspective on the subject.
Practical experience with real-life signals is a key element in understanding and
appreciating biomedical signal analysis. This aspect could be difficult and frustrating
at times, but provides professional satisfaction and educational fun!