Biomedical signal analysis /

• Κύριος συγγραφέας: Rangayyan, Rangaraj M. (Συγγραφέας)
• Μορφή: Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Hoboken, New Jersey : John Wiley & Sons, Inc., 2015.
• Έκδοση: Second edition.
• Σειρά: IEEE Press series in biomedical engineering.
• Θέματα: Signal processing > Data processing.; Diagnostic imaging.; Biomedical engineering.; HEALTH & FITNESS / Holism; HEALTH & FITNESS / Reference; MEDICAL / Alternative Medicine; MEDICAL / Atlases; MEDICAL / Essays; MEDICAL / Family & General Practice; MEDICAL / Holistic Medicine; MEDICAL / Osteopathy; Electronic books.

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 v...

Πίνακας περιεχομένων:

• 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