Chapter 1. Introduction -- Chapter 2. Multifractal study of EEG signal of subjects with Epilepsy and Alzheimer's -- Chapter 3. Multifractal Approach for Quantification of Autonomic Deregulation due to Epileptic Seizure with ECG data -- Chapter 4. Multifractal Analysis of Electromyography data.-Chapter 5. Multifractal study on Parkinson's and Huntington diseases with human gait data -- Chapter 6. Multifractal correlation study between posture and autonomic deregulation using ECG and blood pressure data -- Chapter 7. Appendix.

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. .