Multifractals and Chronic Diseases of the Central Nervous System
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Beschreibung
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.
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 studiesconducted 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.
This book provides a comprehensive study of the various neurological disorders using non-linear dynamics The book primarily focuses on the application of various multifractal methods to studying the physiological signals in different neurological disorders It shows how a multifractal approach can be used to analyze EMG signals in motor neuron disease, which can be developed as a potential biomarker for the diagnosis and prognosis of the disease The book is useful to clinical neurologists, neurosurgeons, neuroscientists and biomedical scientists
Autor*in
Dipak Ghosh
Themen in »Multifractals and Chronic Diseases of the Central Nervous System«
Neurodegenerative diseases Fractal Analytics Multifractals Auto-correlation Cross-correlation Diagnostic Radiology