Advanced Methods of Biomedical Signal Processing

Cover Image Copyright Year: 2011
Author(s): Sergio Cerutti; Carlo Marchesi
Book Type: Wiley-IEEE Press
Content Type : Books & eBooks
Topics: Bioengineering ;  Communication, Networking & Broadcasting ;  Components, Circuits, Devices & Systems ;  Computing & Processing ;  Signal Processing & Analysis
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Abstract

A complete introduction to the application of advanced signal processing methods to biomedical engineering problems

This edited volume, which grew out of the GNB (Gruppo Nazionale di Bioingegneria, Italy) Summer School on Biomedical Signal Processing, explains some of the most advanced methodological signal processing techniques and applies them to biomedical engineering problems. Prominent experts in the areas of biomedical signal processing, biomedical data treatment, medicine, signal processing, system biology, and applied physiology introduce novel techniques and algorithms as well as their clinical or physiological applications.

Divided into seven sections, Advanced Methods of Biomedical Signal Processing covers:

  • The peculiarities of biomedical signal processing with respect to more traditional applications of digital signal processing and their classification

  • An experimental physiologist's and cardiologist's view of the cardiovascular, central and autonomic nervous systems

  • An important link between biomedical signal processing and physiological modeling

  • Time-frequency, time-scale, and wavelet analysis

  • Advanced methods employed in complexity measurements

  • Computational genomics and proteomics

  • Key methods for signal classification, such as neural networks, neuro-fuzzy and genetic algorithms

The book provides a compelling overview of techniques, such as multisource and multi-scale integration of information for physiology and clinical decision; the integration of signal processing methods with a modeling approach; complexity measurement from biomedical signals; higher order analysis in biomedical signals; and classification and parameter enhancement. Various contributions reveal that biomedical signal processing must be viewed in a wider context, with key links to the modeling phase of the signal-generating mechanisms, in order to better comprehend the behavior of the biological system under investigation.

Graduate and PhD students in engineering/biomedical engineering courses, physics and applied mathematics, as well as research professionals in medical and biological sciences will highly benefit from this authoritative resource.

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    Methods of Biomedical Signal Processing: Multiparametric and Multidisciplinary Integration toward a Better Comprehension of Pathophysiological Mechanisms

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    This chapter contains sections titled:

  • Introduction

  • Fundamental Characteristics of Biomedical Signals and Traditional Processing Approaches

  • Link Between Physiological Modeling and Biomedical Signal Processing

  • The Paradigm of Maximum Signal-System Integration

  • Conclusions

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    Data, Signals, and Information: Medical Applications of Digital Signal Processing

    Advanced Methods of Biomedical Signal Processing
    Copyright Year: 2011

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    This chapter contains sections titled:

  • Introduction

  • Characteristic Aspects of Biomedical Signal Processing

  • Utility and Quality of Applications

  • Graphic Methods for Interactively Determining the Most Discriminant Original Variables

  • Alarm Generation

  • Appendix

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    Methods and Neurons

    Advanced Methods of Biomedical Signal Processing
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    This chapter contains sections titled:

  • What is an Object?

  • Which Object Property is Definitely Interesting?

  • Are There Best Techniques?

  • Adaptedness of Techniques

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    Evaluation of the Autonomic Nervous System: From Algorithms to Clinical Practice

    Advanced Methods of Biomedical Signal Processing
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    This chapter contains sections titled:

  • Introduction

  • Relationship Between Heart Rate Variability and Myocardial Infarction

  • Relationship Between Heart Rate Variability and Heart Failure

  • Relationship Between Heart Rate and Blood Pressure Variability

  • Sudden Death Risk Stratification, Prophylactic Treatment, and Unresolved Issues

  • The Role of Autonomic Markers in Noninvasive Risk Stratification

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    Parametric Models for the Analysis of Interactions in Biomedical Signals

    Advanced Methods of Biomedical Signal Processing
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    Wiley-IEEE Press eBook Chapters

    This chapter contains sections titled:

  • Introduction

  • Brief Review of Open-Loop Identification

  • Closed-Loop Identification

  • Applications to Cardiovascular Control

  • Nonlinear Interactions and Synchronization

  • Conclusion

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    Use of Interpretative Models in Biological Signal Processing

    Advanced Methods of Biomedical Signal Processing
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    This chapter contains sections titled:

  • Introduction

  • Mathematical Instruments for Signal Processing

  • Examples

  • Conclusions

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    Multimodal Integration of EEG, MEG, and Functional MRI in the Study Of Human Brain Activity

    Advanced Methods of Biomedical Signal Processing
    Copyright Year: 2011

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    This chapter contains sections titled:

  • Introduction

  • Cortical Activity Estimation from Noninvasive EEG and MEG Measurements

  • Integration of EEG/MEG and fMRI data

  • Appendix I. Electrical Forward Solution for a Realistic Head Model

  • Appendix II. Magnetic Forward Solution

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    Deconvolution for Physiological Signal Analysis

    Advanced Methods of Biomedical Signal Processing
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    This chapter contains sections titled:

  • Introduction

  • Difficulties of the Deconvolution Problem

  • The Regularization Method

  • Other Deconvolution Methods

  • A Stochastic Nonlinear Method for Constrained Problems

  • Conclusions and Developments

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    Linear Time-Frequency Representation

    Advanced Methods of Biomedical Signal Processing
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    This chapter contains sections titled:

  • Introduction

  • The Short-Time Fourier Transform

  • Time-Frequency Resolution

  • Multiresolution Analysis

  • Wavelet Transform

  • A Generalization of the Short-Time Fourier Transform

  • Wavelet Transform and Discrete Filter Banks

  • Matching Pursuit

  • Applications to Biomedical Signals

  • Conclusions

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    Quadratic TimeFrequency Representation

    Advanced Methods of Biomedical Signal Processing
    Copyright Year: 2011

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    This chapter contains sections titled:

  • Introduction

  • A Route to Time-Frequency Representations

  • Wigner-Ville Time-Frequency Representation

  • Interference Terms

  • Cohen's Class

  • Parameter quantification

  • Applications

  • Conclusions

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    Time-Variant Spectral Estimation

    Advanced Methods of Biomedical Signal Processing
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    This chapter contains sections titled:

  • Introduction

  • LMS Methods

  • RLS Algorithm

  • Comparison Between LMS and RLS Methods

  • Different Formulations of the Forgetting Factor

  • Examples and Applications

  • Extension to Multivariate Models

  • Conclusion

  • Appendix 1. Linear Parametric Models

  • Appendix 2. Least Squares Identification

  • Appendix 3. Comparison of Different Forgetting Factors

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    Dynamical Systems and Their Bifurcations

    Advanced Methods of Biomedical Signal Processing
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    This chapter contains sections titled:

  • Dynamical Systems and State Portraits

  • Structural Stability

  • Bifurcations as Collisions

  • Local Bifurcations

  • Global Bifurcations

  • Catastrophes, Hysteresis, and Cusp

  • Routes to Chaos

  • Numerical Methods and Software Packages

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    Fractal Dimension: From Geometry to Physiology

    Advanced Methods of Biomedical Signal Processing
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    This chapter contains sections titled:

  • Geometry

  • Fractal Objects

  • Fractals in Physiology

  • Hurst Exponent

  • Concluding Remarks

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    Nonlinear Analysis of Experimental Time Series

    Advanced Methods of Biomedical Signal Processing
    Copyright Year: 2011

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    This chapter contains sections titled:

  • Introduction

  • Reconstruction in the Embedding Space

  • Testing for Nonlinearity with Surrogate Data

  • Estimation of Invariants: Fractal Dimension and Lyapunov Exponents

  • Dimension of Kaplan and Yorke

  • Entropy

  • Nonlinear Noise Reduction

  • Conclusion

  • Appendix

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    Blind Source Separation: Application to Biomedical Signals

    Advanced Methods of Biomedical Signal Processing
    Copyright Year: 2011

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    This chapter contains sections titled:

  • Introduction

  • Mathematical Models of Mixtures

  • Processing Techniques

  • Applications

  • Appendix

  • Acknowledgments

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    Higher Order Spectra

    Advanced Methods of Biomedical Signal Processing
    Copyright Year: 2011

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    This chapter contains sections titled:

  • Introduction

  • Higher Order Statistics: Definition and Main Properties

  • Bispectrum and Bicoherence: Definitions, Properties, and Estimation Methods

  • Analysis of Nonlinear Signals: Quadratic Phase Coupling

  • Identification of Linear Systems

  • Interaction Among Cardiorespiratory Signals

  • Clinical Applications of HOS: Bispectral Index for Assessment of Anaesthesia Depth

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    Molecular Bioengineering and Nanobioscience: Data Analysis and Processing Methods

    Advanced Methods of Biomedical Signal Processing
    Copyright Year: 2011

    Wiley-IEEE Press eBook Chapters

    This chapter contains sections titled:

  • Introduction

  • Data Analysis and Processing Methods for Genomics in the Postgenomic Era

  • From Genomics to Proteomics

  • Protein Structure Determination

  • Conclusions

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    Microarray Data Analysis: General Concepts, Gene Selection, and Classification

    Advanced Methods of Biomedical Signal Processing
    Copyright Year: 2011

    Wiley-IEEE Press eBook Chapters

    This chapter contains sections titled:

  • Introduction

  • From Microarray to Gene Expression Data

  • Identification of Differentially Expressed Genes

  • Classification: Unsupervised Methods

  • Classification: Supervised Methods

  • Conclusions

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    Microarray Data Analysis: Gene Regulatory Networks

    Advanced Methods of Biomedical Signal Processing
    Copyright Year: 2011

    Wiley-IEEE Press eBook Chapters

    This chapter contains sections titled:

  • Introduction

  • Boolean Models

  • Differential Equation Models

  • Bayesian Models

  • Conclusions

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    Biomolecular Sequence Analysis

    Advanced Methods of Biomedical Signal Processing
    Copyright Year: 2011

    Wiley-IEEE Press eBook Chapters

    This chapter contains sections titled:

  • Introduction

  • Correlation in DNA Sequences

  • Spectral Methods in Genomics

  • Information Theory

  • Processing of Protein Sequences

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    Soft Computing in Signal and Data Analysis: Neural Networks, NeuroFuzzy Networks, and Genetic Algorithms

    Advanced Methods of Biomedical Signal Processing
    Copyright Year: 2011

    Wiley-IEEE Press eBook Chapters

    This chapter contains sections titled:

  • Introduction

  • Adaptive Networks

  • Neural Networks

  • Learning

  • Structural Adaptation

  • Neuro-Fuzzy Networks

  • Genetic Algorithms

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    Interpretation and Classification of Patient Status Patterns

    Advanced Methods of Biomedical Signal Processing
    Copyright Year: 2011

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    This chapter contains sections titled:

  • The Classification Process

  • The Bayes Classifier

  • A Different Approach to Interpret (and Classify) Data: Cluster Analysis

  • Applications to Biomedical Data

  • Visual Exploration of Biomedical Data

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    Index

    Advanced Methods of Biomedical Signal Processing
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    IEEE Press Series in Biomedical Engineering

    Advanced Methods of Biomedical Signal Processing
    Copyright Year: 2011

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