2nd Edition

Signals and Systems Analysis In Biomedical Engineering

By Robert B. Northrop Copyright 2010
    654 Pages 215 B/W Illustrations
    by CRC Press

    The first edition of this text, based on the author’s 30 years of teaching and research on neurosensory systems, helped biomedical engineering students and professionals strengthen their skills in the common network of applied mathematics that ties together the diverse disciplines that comprise this field. Updated and revised to include new material as the field has grown, Signals and Systems Analysis in Biomedical Engineering, Second Edition continues to provide a ready source of information on those specialized mathematical techniques most useful in describing and analyzing biomedical signals.

    New chapters on nonlinear and complex systems

    Enriched with many examples that promote sound practical analysis, this volume covers classical linear systems theory and its applications to biomedicine. It examines the important use of joint time-frequency analysis to characterize non-stationary physiological signals, and explores the mathematics of tomographic imaging (the Radon transform, the Fourier slice theorem, and the filtered back-projection algorithm). It also describes the analytical signal and the Hilbert transform and some of its biomedical applications. New chapters in this edition include one on the analysis of nonlinear biochemical systems and biochemical oscillators, as well as one introducing complex systems and illustrating ways to best model them.

    Four appendices with additional material

    Extensive appendices supplement the text, including "Simnon® Programs Used in Chapters 11 and 12," "How to use Root Locus to Determine the Stability of SISO Linear Systems," "Signal Flow Graphs and Mason’s Rule," and "Computational Tools for Biomedical Signal Processing and Systems Analysis." An extensive glossary is included as well as an ample listing of sources for further study.

    Introduction to Biomedical Signals and Systems
    General Characteristics of Biomedical Signals
    General Properties of PSs
    Review of Linear Systems Theory
    Linearity, Causality, and Stationarity
    Analog Systems
    Systems Described by Sets of ODEs
    Linear System Characterization
    Discrete Signals and Systems
    Stability of Systems
    The Laplace Transform and Its Applications
    Properties of the Laplace Transform
    Some Examples of Finding Laplace Transforms
    The Inverse Laplace Transform
    Applications of the Laplace Transform
    Fourier Series Analysis of Periodic Signals
    Properties of the FS
    FS Examples
    The Continuous Fourier Transform
    Properties of the CFT
    ADC and the Sampling Theorem
    The Analytical Signal and the HT
    MTF in Imaging
    The Discrete Fourier Transform
    The CFT, ICFT, DFT, and IDFT
    Data Window Functions
    The FFT
    Introduction to Joint TimeFrequency Analysis of Biomedical Signals
    The Short-Term Fourier Transform
    The Gabor and Adaptive Gabor Transforms
    The WignerVille and PseudoWigner Transforms
    Cohen’s General Class of JTF Distributions
    Introduction to JTFA Using Wavelets
    Applications of JTFA to Physiological Signals
    JTFA Software
    Introduction to the Analysis of Stationary Noise, and Signals Contaminated with Noise
    Noise Descriptors and Noise in Systems
    Calculation of Noise Descriptors with Finite Discrete Data
    Signal Averaging and Filtering for SNR Improvement
    Introduction to the Application of Statistics and IT to Genomics
    Basic Mathematical Tools Used in the Characterization of Physiological Systems
    Some General Properties of PSs
    Some Properties of Nonlinear Systems
    Physical Factors Determining the Dynamic Behavior of PSs
    Means of Characterizing PSs
    Introduction to the Mathematics of Tomographic Imaging
    Algebraic Reconstruction
    The Radon Transform
    The Fourier Slice Theorem
    Filtered BackProjection Algorithm
    Introduction to the Analysis of Nonlinear Biochemical Systems and Biochemical Oscillators
    Introduction: Some General Properties of Nonlinear Systems
    All Living Systems Are Nonlinear
    Parametric Regulation in Nonlinear Biological Systems
    Approaches to Nonlinear Analysis: the Phase Plane
    Chaos, Stability, and Limit Cycles in Nonlinear Biological Systems
    Introduction to Complex Systems in Biology and Medicine
    Introduction to Complex Systems
    When Is a System Complex?
    Some Examples
    Properties of Complex Systems: Chaos and Tipping Points
    The Law of Unintended Consequences
    Why Study Complex Systems?
    Human Responses to Complexity
    Complex Systems Engineering
    Some Complex Physiological Regulatory Systems
    Structure and Function: Some Examples of Complex Physiological Regulatory Systems and Their Simplified Models
    Examples of When Complex Physiological Systems Fail
    Some Approaches to Dealing with Complexity in an Organized Manner
    Appendix A
    Appendix B
    Appendix C
    Appendix D


    Robert B. Northrop graduated with a bachelor’s degree in electrical engineering from the Massachusetts Institute of Technology in 1956. At the University of Connecticut (UCONN), he received a master’s degree in systems engineering in 1958. As the result of a long-standing interest in physiology, he entered a PhD program at UCONN in physiology, doing research on the neuromuscular physiology of molluskan catch muscles. He received his PhD in 1964. His current research interest lies in complex systems. Dr. Northrop was on the electrical and computer engineering faculty at UCONN until his retirement in June 1997. Throughout this time, he was director of the BME graduate program. As emeritus professor, he still teaches courses in BME, writes texts, sails, and travels. He lives in Chaplin, CT, with his wife, and a smooth fox terrier.