Dipak Ghosh – författare

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 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 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.