Biomedical Signal Analysis

✍ Scribed by Rangayyan, Rangaraj M.

• Publisher: Wiley
• Year: 2015
• Tongue: English
• Leaves: 717
• Series: IEEE Press series in biomedical engineering.
• Edition: 2nd ed.
• Category: Library

✦ Synopsis

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

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✦ Table of Contents

BIOMEDICAL SIGNAL ANALYSIS
Dedication
Contents
Preface
Acknowledgments
Preface: First Edition
Acknowledgments: First Edition
About the Author
Symbols and Abbreviations
1 Introduction to Biomedical Signals
1.1 The Nature of Biomedical Signals
1.2 Examples of Biomedical Signals
1.2.1 The action potential of a cardiac myocyte
1.2.2 The action potential of a neuron
1.2.3 The electroneurogram (ENG)
1.2.4 The electromyogram (EMG)
1.2.5 The electrocardiogram (ECG)
1.2.6 The electroencephalogram (EEG)
1.2.7 Eventrelated potentials (ERPs)
1.2.8 The electrogastrogram (EGG) 1.2.9 The phonocardiogram (PCG)1.2.10 The carotid pulse
1.2.11 Signals from catheter tip sensors
1.2.12 The speech signal
1.2.13 The vibromyogram (VMG)
1.2.14 The vibroarthrogram (VAG)
1.2.15 Otoacoustic emission (OAE) signals
1.2.16 Bioacoustic signals
1.3 Objectives of Biomedical Signal Analysis
1.4 Difficulties in Biomedical Signal Analysis
1.5 Why Use CAD?
1.6 Remarks
1.7 Study Questions and Problems
1.8 Laboratory Exercises and Projects
2 Concurrent, Coupled, and Correlated Processes
2.1 Problem Statement
2.2 Illustration of the Problem with Case Studies 2.2.1 The ECG and the PCG2.2.2 The PCG and the carotid pulse
2.2.3 The ECG and the atrial electrogram
2.2.4 Cardiorespiratory interaction
2.2.5 The importance of HRV
2.2.6 The EMG and VMG
2.2.7 The knee joint and muscle vibration signals
2.3 Application: Segmentation of the PCG
2.4 Application: Diagnosis and Monitoring of Sleep Apnea
2.4.1 Monitoring of sleep apnea by polysomnography
2.4.2 Home monitoring of sleep apnea
2.4.3 Multivariate and multiorgan analysis
2.5 Remarks
2.6 Study Questions and Problems
2.7 Laboratory Exercises and Projects 3 Filtering for Removal of Artifacts3.1 Problem Statement
3.2 Random, Structured, and Physiological Noise
3.2.1 Random noise
3.2.2 Structured noise
3.2.3 Physiological interference
3.2.4 Stationary, nonstationary, and cyclostationary processes
3.3 Illustration of the Problem with Case Studies
3.3.1 Noise in event related potentials
3.3.2 High frequency noise in the ECG
3.3.3 Motion artifact in the ECG
3.3.4 Powerline interference in ECG signals
3.3.5 Maternal interference in fetal ECG
3.3.6 Muscle contraction interference in VAG signals
3.3.7 Potential solutions to the problem 3.4 Fundamental Concepts of Filtering3.4.1 Linear shift invariant filters
3.4.2 Transform domain analysis of signals and systems
3.4.3 The pole-zero plot
3.4.4 The discrete Fourier transform
3.4.5 Properties of the Fourier transform
3.5 Time domain Filters
3.5.1 Synchronized averaging
3.5.2 MA filters
3.5.3 Derivative based operators to remove low frequency artifacts
3.5.4 Various specifications of a filter
3.6 Frequency domain Filters
3.6.1 Removal of high frequency noise: Butterworth lowpass filters
3.6.2 Removal of low frequency noise: Butterworth highpass filters

✦ Subjects

Медицинские дисциплины;Медицинские приборы и аппараты;