BookDipak Ghosh, Shukla Samanta, Sayantan Chakraborty.
Summary: This book primarily focuses on the study of various neurological disorders, including Parkinson's (PD), Huntington (HD), Epilepsy, Alzheimer's and Motor Neuron Diseases (MND) from a new perspective by analyzing the physiological signals associated with them using non-linear dynamics. The development of nonlinear methods has significantly helped to study complex nonlinear systems in detail by providing accurate and reliable information. The book provides a brief introduction to the central nervous system and its various disorders, their effects on health and quality of life, and their respective courses of treatment, followed by different bioelectrical signals like those detected by Electroencephalography (EEG), Electrocardiography (ECG), and Electromyography (EMG). In turn, the book discusses a range of nonlinear techniques, fractals, multifractals, and Higuchi's Fractal Dimension (HFD), with mathematical examples and procedures. A review of studies conducted to date on neurological disorders like epilepsy, dementia, Parkinson's, Huntington, Alzheimer's, and Motor Neuron Diseases, which incorporate linear and nonlinear techniques, is also provided. The book subsequently presents new findings on neurological disorders of the central nervous system, namely Parkinson's disease and Huntington's disease, by analyzing their gait characteristics using a nonlinear fractal based technique: Multifractal Detrended Fluctuation Analysis (MFDFA). In closing, the book elaborates on several parameters that can be obtained from cross-correlation studies of ECG and blood pressure, and can be used as markers for neurological disorders.
Contents:
Chapter 1: Introduction; 1.1 Central Nervous System and Its Diseases; 1.2 Bioelectrical Signals; 1.2.1 Electroencephalography; 1.2.2 Electrocardiography; 1.2.3 Electromyography; 1.3 Linear Signal Processing Techniques; 1.3.1 Root Mean Square (RMS) Method; 1.3.2 Fast Fourier Transform (FFT) Method; 1.3.3 Short-Time Fourier Transform (STFT) Method; 1.3.4 Wavelet Transform (WT) Method; 1.3.5 Discrete Wavelet Transform (DWT) Method; 1.4 Limitations of Linear Analysis Techniques; 1.5 Non-linear Techniques 1.5.1 Fractals and Multifractals1.5.1.1 Detrended Fractal Analysis; 1.5.2 Non-linear Analysis of Biomedical Signals; 1.5.2.1 Non-linear Analysis of EEG Signals; 1.5.2.2 Non-linear Analysis of ECG Signals; 1.5.2.3 Non-linear Analysis of EMG Signals; 1.6 Review of Studies on Neurological Disorders; 1.6.1 Epilepsy; 1.6.2 Dementia (Alzheimerś Disease); 1.6.3 Parkinsonś Disease; 1.6.4 Huntingtonś Disease; 1.6.5 Motor Neuron Disease (MND); References; Chapter 2: Multifractal Study of EEG Signal of Subjects with Epilepsy and Alzheimerś; 2.1 Introduction 2.2 Neurological Disorder: Epilepsy, Alzheimerś, and EEG Data2.2.1 Epilepsy; 2.2.2 Alzheimerś Disease; 2.2.3 EEG Data; 2.3 Multifractal Detrended Fluctuation Analysis of EEG Signals; 2.4 Multifractal Detrended Cross-Correlation Analysis of EEG Signals; 2.5 Possible Application as Biomarker of Epilepsy; References; Chapter 3: Multifractal Approach for Quantification of Autonomic Deregulation Due to Epileptic Seizure with ECG Data; 3.1 Introduction; 3.2 Systematic Studies on Abnormalities in Cardiac Autonomic Status; 3.3 Multifractal Detrended Fluctuation Analysis of ECG Signals 3.3.1 ECG Data3.4 Results and Possible Biomarker; References; Chapter 4: Multifractal Analysis of Electromyography Data; 4.1 Introduction; 4.2 Motor Neuron and Musculoskeletal Disease: Neuropathy and Myopathy; 4.3 Electromyography
A Tool to Detect Motor Neuron Disease; 4.4 Study of SEMG Signals; 4.5 Electromyography Data; 4.6 Multifractal Detrended Fluctuation Analysis of EMG Signals; 4.7 Results and Possible Advanced Level Biomarker; References; Chapter 5: Multifractal Study of Parkinsonś and Huntingtonś Diseases with Human Gait Data; 5.1 Introduction 5.2 Parkinsonś Disease and Gait Data5.2.1 Gait Data; 5.3 Multifractal and Multifractal Cross-Correlation Analysis of Parkinsonś Disease; 5.4 Huntingtonś Disease and Gait Data; 5.5 Multifractal Analysis of Huntingtonś Data; 5.6 Discussions on Possible Use of the Result for Biomarkers of Parkinsonś and Huntingtonś; References; Chapter 6: Multifractal Correlation Study Between Posture and Autonomic Deregulation Using ECG and Blood Pressure Data; 6.1 Introduction; 6.1.1 Blood Pressure; 6.1.2 Non-linear Heart Rate Variability Analysis