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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 addresses the acoustic signal analysis and spectral
dynamics of the tanpura, an Indian plucked string instrument. In
addition, it strives to provide a logical and objective explanation
of Indian classical musicians' cognitive experience. Issues of
relevance in this regard include the rich, mellifluous sound; the
undulation of the loudness; the somewhat cyclical variation of the
timbre, which is strongly related to these undulations; and the
occasional perception of virtual notes to which no strings are
tuned. The book analyses the materials used in the tanpura, the
instrument's simple structure, the intricacies of the lower bridge,
and the theory of string vibration with variable string length.
Cognitive experiments to provide the basis for perceptual quality
assessment, as well as a methodology for ranking, are described.
This is followed by acoustic analyses, both temporal and spectral,
for sounds produced by male and female tanpuras, for each
individual string and the combined one. An important aspect related
to the naturalness of perceived sound, namely the intrinsically
associated random perturbations, is also discussed. The apparent
irregularities perceived in the acoustic signal produced by the
tanpura reveal the importance of examining the signal from the
perspective of non-linear analysis, an aspect that is also covered
in the book. Given its scope, the book will appeal to students and
researchers in the fields of music acoustics, artificial
intelligence, and cognitive science, as well as musicians and
musicologists around the world.
This book provides a comprehensive overview of how fractal
analytics can lead to the extraction of interesting features from
the complex electroencephalograph (EEG) signals generated by
Hindustani classical music. It particularly focuses on how the
brain responses to the emotional attributes of Hindustani classical
music that have been long been a source of discussion for
musicologists and psychologists. Using robust scientific techniques
that are capable of looking into the most intricate dynamics of the
complex EEG signals, it deciphers the human brain's response to
different ragas of Hindustani classical music, shedding new light
on what happens inside the performer's brain when they are mentally
composing the imagery of a particular raga. It also explores the
much- debated issue in the musical fraternity of whether there are
any universal cues in music that make it identifiable for people
throughout the world, and if so, what are the neural correlates
associated with the universal cues? This book is of interest to
researchers and scholars of music and the brain, nonlinear science,
music cognition, music signal processing and music information
retrieval. In addition, researchers in the field of nonlinear
biomedical signal processing and music signal analysis benefit from
this book.
This book provides a comprehensive overview of how fractal
analytics can lead to the extraction of interesting features from
the complex electroencephalograph (EEG) signals generated by
Hindustani classical music. It particularly focuses on how the
brain responses to the emotional attributes of Hindustani classical
music that have been long been a source of discussion for
musicologists and psychologists. Using robust scientific techniques
that are capable of looking into the most intricate dynamics of the
complex EEG signals, it deciphers the human brain's response to
different ragas of Hindustani classical music, shedding new light
on what happens inside the performer's brain when they are mentally
composing the imagery of a particular raga. It also explores the
much- debated issue in the musical fraternity of whether there are
any universal cues in music that make it identifiable for people
throughout the world, and if so, what are the neural correlates
associated with the universal cues? This book is of interest to
researchers and scholars of music and the brain, nonlinear science,
music cognition, music signal processing and music information
retrieval. In addition, researchers in the field of nonlinear
biomedical signal processing and music signal analysis benefit from
this book.
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