| Description |
1 online resource (191 pages) |
| Series |
Online access with DDA: Askews (Maths)
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| Contents |
Cover; Half Title; Title Page; Copyright Page; Preface; Table of Contents; List of Figures; 1: Introduction; Abstract; 1.1 Introduction; 1.2 History of Fractal Analysis; 1.3 Fundamentals of Fractals; 1.4 Definition of Fractal; 1.5 Complexity of Biological Systems; 1.6 Fractal Dimension; 1.7 Summary of this Book; References; 2: Physiology, Anatomy and Fractal Properties; Abstract; 2.1 Introduction; 2.2 Conceptual Understanding; 2.3 Chaos, Complexity, Fractals and Entropy; 2.4 Chaos Theory; 2.5 Complex Systems; 2.6 Entropy; 2.7 Fractal and Fractal Dimension; 2.8 Computing Fractal Dimension |
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2.8.1 Box-counting2.8.2 Power spectrum fractal dimension; 2.9 Relationship of Fractals and Self-similarity; 2.9.1 Sierpinski triangle; 2.9.2 Fractal dimension of the Menger Sponge; 2.10 Fractals in Biology; 2.11 Properties of Natural and Synthetic Objects; 2.12 Human Physiology; 2.12.1 Fractals and Electrocardiogram (ECG), Electromyogram (EMG) and Electroencephalogram (EEG); 2.12.2 Fractal dimension for human movement and gait analysis; 2.13 Summary; References; 3: Fractal Dimension of Biosignals; Abstract; 3.1 Introduction; 3.2 Fractal Dimension and Self-similarity; 3.2.1 Self-similarity |
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Exact self-similarityApproximate self-similarity; Statistical self-similarity; 3.2.2 Fractal dimension; 3.3 Different Methods to Estimate Fractal Dimension of a Waveform; 3.3.1 Box-counting method; 3.3.2 Katz's algorithm; 3.3.3 Higuchi's algorithm; 3.3.4 Petrosian's algorithm; 3.3.5 Sevcik's algorithm; 3.3.6 Correlation dimension; 3.3.7 Adapted box fractal dimension; 3.3.8 Fractal dimension estimate based on power law function; 3.4 Fractals and Electrocardiogram (ECG), Electromyogram (EMG) and Electroencephalogram (EEG); 3.5 Fractal Dimension for Gait Analysis; 3.5.1 Example; 3.6 Summary |
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5.2.2 Factors that influence sEMG5.2.3 Signal features of sEMG; Amplitude analysis; Spectral analysis; Statistical and chaos based features; 5.3 Fractal Analysis of sEMG; 5.3.1 Self-similarity of sEMG; 5.3.2 Algorithms to compute fractal dimension of sEMG; Signals in the time domain; Signals in the phase space domain; 5.3.3 Fractal features of sEMG; 5.4 Summary; References; 6: Fractals Analysis of Electroencephalogram; Abstract; 6.1 Introduction; 6.1.1 History of EEG; 6.1.2 Fundamentals of EEG; 6.2 Techniques for EEG Analysis; 6.3 Fractal Properties of EEG |
| Summary |
The book provides an insight into the advantages and limitations of the use of fractals in biomedical data. It begins with a brief introduction to the concept of fractals and other associated measures and describes applications for biomedical signals and images. Properties of biological data in relations to fractals and entropy, and the association with health and ageing are also covered. The book provides a detailed description of new techniques on physiological signals and images based on the fractal and chaos theory. The aim of this book is to serve as a comprehensive guide for researchers and readers interested in biomedical signal and image processing and feature extraction for disease risk analyses and rehabilitation applications. While it provides the mathematical rigor for those readers interested in such details, it also describes the topic intuitively such that it is suitable for audience who are interested in applying the methods to healthcare and clinical applications. The book is the outcome of years of research by the authors and is comprehensive and includes other reported outcomes |
| Bibliography |
References4: Fractals Analysis of Electrocardiogram; Abstract; 4.1 Introduction; 4.1.1 Recording cardiac activity; 4.2 Heart Rate Variability; 4.2.1 Computing heart rate variability; 4.3 Fractal Properties of ECG; 4.4 An Example; 4.5 Poincaré Plot of Heart-rate Variability; 4.6 Application-ECG and Heart Rate Variability; Time domain analysis; Frequency domain analysis; Poincaré analysis; Fractal dimension; 4.7 Summary; References; 5: Fractals Analysis of Surface Electromyogram; Abstract; 5.1 Introduction; 5.2 Surface Electromyogram (sEMG) ; 5.2.1 Principles of sEMG |
| Notes |
6.4 An Example-Measuring Alertness Using Fractal Properties of EEG |
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Print version record |
| Subject |
Fractals.
|
|
fractals.
|
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Fractals.
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| Form |
Electronic book
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| Author |
Arjunan, Sridhar P
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Aliahmad, Behzad
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| ISBN |
9781351678384 |
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1351678388 |
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9781498744225 |
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1498744222 |
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9781498744218 |
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1498744214 |
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