Nonlinear Dynamic Modeling of Physiological Systems (IEEE Press Series on Biomedical Engineering) [Hardcover]

Professor Vasilis Z. Marmarelis (Author)

Book Description

ISBN-10: 0471469602 | ISBN-13: 978-0471469605 | Publication Date: September 3, 2004 | Edition: 1

The study of nonlinearities in physiology has been hindered by the lack of effective ways to obtain nonlinear dynamic models from stimulus-response data in a practical context. A considerable body of knowledge has accumulated over the last thirty years in this area of research. This book summarizes that progress, and details the most recent methodologies that offer practical solutions to this daunting problem. Implementation and application are discussed, and examples are provided using both synthetic and actual experimental data.
This essential study of nonlinearities in physiology apprises researchers and students of the latest findings and techniques in the field.

Editorial Reviews

Review

"...a perfect research tool, as reference book, and even as a textbook. I highly recommend it to everyone interested in nonlinear dynamics." (Journal of Intelligent & Fuzzy Systems, Vol. 16, No. 2, 2005)

"...a well-written methodology book...a useful addition to [researchers, engineers and graduate students']...personal libraries." (E-STREAMS, September 2005)

From the Back Cover

A practical approach to obtaining nonlinear dynamic models from stimulus-response data

Nonlinear modeling of physiological systems from stimulus-response data is a long-standing problem that has substantial implications for many scientific fields and associated technologies. These disciplines include biomedical engineering, signal processing, neural networks, medical imaging, and robotics and automation. Addressing the needs of a broad spectrum of scientific and engineering researchers, this book presents practicable, yet mathematically rigorous methodologies for constructing dynamic models of physiological systems.

Nonlinear Dynamic Modeling of Physiological Systems provides the most comprehensive treatment of the subject to date. Starting with the mathematical background upon which these methodologies are built, the book presents the methodologies that have been developed and used over the past thirty years. The text discusses implementation and computational issues and gives illustrative examples using both synthetic and experimental data. The author discusses the various modeling approaches–nonparametric, including the Volterra and Wiener models; parametric; modular; and connectionist–and clearly identifies their comparative advantages and disadvantages along with the key criteria that must guide successful practical application. Selected applications covered include neural and sensory systems, cardiovascular and renal systems, and endocrine and metabolic systems.

This lucid and comprehensive text is a valuable reference and guide for the community of scientists and engineers who wish to develop and apply the skills of nonlinear modeling to physiological systems.

See all Editorial Reviews

Product Details

• Hardcover: 541 pages
• Publisher: Wiley-IEEE Press; 1 edition (September 3, 2004)
• Language: English
• ISBN-10: 0471469602
• ISBN-13: 978-0471469605
• Product Dimensions: 10.2 x 7.3 x 1.2 inches
• Shipping Weight: 2.4 pounds (View shipping rates and policies)
• Average Customer Review: 4.3 out of 5 stars  See all reviews (3 customer reviews)
• Amazon Best Sellers Rank: #2,276,467 in Books (See Top 100 in Books)

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Most Helpful Customer Reviews

1 of 1 people found the following review helpful:

5.0 out of 5 stars The only well-writen up-to-date book for nonlinear modeling, June 23, 2005

By 

Theodoros Zanos (Los Angeles, CA, USA) - See all my reviews
(REAL NAME)   

This review is from: Nonlinear Dynamic Modeling of Physiological Systems (IEEE Press Series on Biomedical Engineering) (Hardcover)

The book gives an introduction, as well as a more in-depth look on a number of parametric and nonparametric modeling approaches, as well as their applications to modern physiological system modeling, focusing on the nonlinearies and nonstationarities that need to be addressed during this approach. Although one must be equipped with sufficient understanding of signal processing and a strong mathematic background to access the field of nonlinear modeling, this book is as accessible as it can get, providing constantly examples and applications for each concept it introduces.

5.0 out of 5 stars Great book on nonlinear physiological modeling, October 28, 2011

By 

Flavia Maria Guerra de Sousa - See all my reviews

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This review is from: Nonlinear Dynamic Modeling of Physiological Systems (IEEE Press Series on Biomedical Engineering) (Hardcover)

It is a great book for those interested in effective methodological tools for mathematical modeling of nonlinear physiological systems. The book begins by presenting an overview of the physiological system modeling problem with several examples (e.g. vertebrate retina, invertebrate photoreceptor, glucose-insulin minimal model). The author was personally involved in the investigation of many of these models, which makes the presentation and interpretation of the obtained results particularly interesting. This is followed by presentation of the concept of a functional as a mathematical mapping of the past and present values of the input signal x(t) onto the present value of the output signal y(t). This functional representation using input-output physiological data is used for the nonparametric dynamic modeling of nonlinear physiological systems, based on the Volterra functional expansion and its variants (e.g. orthogonal Wiener series). The advantages and limitations of the different models are discussed. The Laguerre expansion technique for Volterra kernel estimation is then presented as a means of significantly reducing the total number of parameters to be estimated, which has the advantage of not only reducing the computational burden of the identification process, but also allowing the use of shorter data sets in the identification process. This is especially interesting when dealing with human physiological data, as is my case, since it allows the possibility of reducing the duration of a particular study and still obtaining meaningful results.

The book focuses on the interpretation of the estimated kernels obtained throughout the book, in particular the first- and second-order kernels, as a means of obtaining dynamic information of the system being studied (e.g. the first order kernels in the time domain are related to the dynamic relationships between past values of the input(s) and the linear component of the output, while the second order kernels investigate the dynamic inter-relationships among pairs of input variables to the quadratic component of the system output). While this first part of the book is my personal main interest at this time (my current work involves the identification of physiologically meaningful parameters in a minimal cardiorespiratory model using the Laguerre expansion technique and its variants), the book also discusses parametric (including the NARMAX model), modular (including the principal dynamic modes of a system, equivalent to the discrete Volterra model), and connectionist models, as well as the modeling of multiinput/multioutput systems and closed-loop systems.

I would recommend this book to anyone interested in a thorough understanding of the identification process of nonlinear physiological models.

3.0 out of 5 stars If you get past the ego of the author, this is a great book, January 20, 2009

By 

Neurofox "Neurofox" - See all my reviews

This review is from: Nonlinear Dynamic Modeling of Physiological Systems (IEEE Press Series on Biomedical Engineering) (Hardcover)

Really. Highly recommended. For getting started in this field.

But some of the hyperbole is rather off-putting.