Описание: Biomedical signals provide unprecedented insight into abnormal or anomalous neurological conditions. The computer-aided diagnosis (CAD) system plays a key role in detecting neurological abnormalities and improving diagnosis and treatment consistency in medicine. This book covers different aspects of biomedical signals-based systems used in the automatic detection/identification of neurological disorders. Several biomedical signals are introduced and analyzed, including electroencephalogram (EEG), electrocardiogram (ECG), heart rate (HR), magnetoencephalogram (MEG), and electromyogram (EMG). It explains the role of the CAD system in processing biomedical signals and the application to neurological disorder diagnosis. The book provides the basics of biomedical signal processing, optimization methods, and machine learning/deep learning techniques used in designing CAD systems for neurological disorders.
Автор: Adeli Название: Automated EEG-Based Diagnosis of Neurological Disorders ISBN: 1138118206 ISBN-13(EAN): 9781138118201 Издательство: Taylor&Francis Рейтинг: Цена: 11023.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Based on the authors' groundbreaking research, Automated EEG-Based Diagnosis of Neurological Disorders: Inventing the Future of Neurology presents a research ideology, a novel multi-paradigm methodology, and advanced computational models for the automated EEG-based diagnosis of neurological disorders. It is based on the ingenious integration of three different computing technologies and problem-solving paradigms: neural networks, wavelets, and chaos theory. The book also includes three introductory chapters that familiarize readers with these three distinct paradigms.
After extensive research and the discovery of relevant mathematical markers, the authors present a methodology for epilepsy diagnosis and seizure detection that offers an exceptional accuracy rate of 96 percent. They examine technology that has the potential to impact and transform neurology practice in a significant way. They also include some preliminary results towards EEG-based diagnosis of Alzheimer's disease.
The methodology presented in the book is especially versatile and can be adapted and applied for the diagnosis of other brain disorders. The senior author is currently extending the new technology to diagnosis of ADHD and autism. A second contribution made by the book is its presentation and advancement of Spiking Neural Networks as the seminal foundation of a more realistic and plausible third generation neural network.
Автор: Nikolaos S. Voros; Christos P. Antonopoulos Название: Cyberphysical Systems for Epilepsy and Related Brain Disorders ISBN: 3319200488 ISBN-13(EAN): 9783319200484 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces a new cyberphysical system that combines clinical and basic neuroscience research with advanced data analysis and medical management tools for developing novel applications for the management of epilepsy.
Автор: Kumar, Nilesh Название: EEG-Based Diagnosis of Alzheimer Disease ISBN: 012815392X ISBN-13(EAN): 9780128153925 Издательство: Elsevier Science Рейтинг: Цена: 15487.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: EEG-Based Diagnosis of Alzheimer Disease: A Review and Novel Approaches for Feature Extraction and Classification Techniques provides a practical and easy-to-use guide for researchers in EEG signal processing techniques, Alzheimer’s disease, and dementia diagnostics. The book examines different features of EEG signals used to properly diagnose Alzheimer’s Disease early, presenting new and innovative results in the extraction and classification of Alzheimer’s Disease using EEG signals. This book brings together the use of different EEG features, such as linear and nonlinear features, which play a significant role in diagnosing Alzheimer’s Disease.
Описание: Computer-aided design (CAD) plays a key role in improving biomedical systems for various applications. It also helps in the detection, identification, predication, analysis, and classification of diseases, in the management of chronic conditions, and in the delivery of health services. This book discusses the uses of CAD to solve real-world problems and challenges in biomedical systems with the help of appropriate case studies and research simulation results. Aiming to overcome the gap between CAD and biomedical science, it describes behaviors, concepts, fundamentals, principles, case studies, and future directions for research, including the automatic identification of related disorders using CAD. Features:Proposes CAD for the study of biomedical signals to understand physiology and to improve healthcare systems’ ability to diagnose and identify health disorders. Presents concepts of CAD for biomedical modalities in different disorders. Discusses design and simulation examples, issues, and challenges. Illustrates bio-potential signals and their appropriate use in studying different disorders. Includes case studies, practical examples, and research directions. Computer-Aided Design and Diagnosis Methods for Biometrical Applications is aimed at researchers, graduate students in biomedical engineering, image processing, biomedical technology, medical imaging, and health informatics.
Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more.
This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis.
Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction
Explains how to apply machine learning techniques to EEG, ECG and EMG signals
Gives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series
Автор: Semmlow, John Название: Circuits, Signals and Systems for Bioengineers ISBN: 0128093951 ISBN-13(EAN): 9780128093955 Издательство: Elsevier Science Рейтинг: Цена: 15999.00 р. Наличие на складе: Нет в наличии.
Описание:
Circuits, Signals and Systems for Bioengineers: A MATLAB-Based Introduction, Third Edition, guides the reader through the electrical engineering principles that can be applied to biological systems. It details the basic engineering concepts that underlie biomedical systems, medical devices, biocontrol and biomedical signal analysis, providing a solid foundation for students in important bioengineering concepts.
Fully revised and updated to better meet the needs of instructors and students, the third edition introduces and develops concepts through computational methods that allow students to explore operations, such as correlations, convolution, the Fourier transform and the transfer function. New chapters have been added on image analysis, noise, stochastic processes and ergodicity, and new medical examples and applications are included throughout the text.
Covers current applications in biocontrol, with examples from physiological systems modeling, such as the respiratory system
Includes revised material throughout, with improved clarity of presentation and more biological, physiological and medical examples and applications
Includes a new chapter on noise, stochastic processes, non-stationary and ergodicity
Includes a separate new chapter featuring expanded coverage of image analysis
Includes support materials, such as solutions, lecture slides, MATLAB data and functions needed to solve the problems
Описание: This book provides an outline of epigenetics as a whole, while also specifically examining a range of epigenetic players, including histone acetyl transferases (HATs) and histone deacetylases (HDACs). It chiefly focuses on the emerging targets of HDACs and their implications for various neurological disorders, while also discussing the drawbacks of current therapeutic strategies, the classification of HDAC inhibitors, and their promising effects in connection with specific neurological disorders. The book explores the potential use of these inhibitors as novel therapeutic agents, considers the current challenges involved in using them to tackle neurological complications, and offers a novel solution by designing isoform-selective inhibitors and employing combinatorial therapeutic strategies. Its final section, which explores future directions, elaborates on the possibility of enhancing HDAC inhibitors’ therapeutic efficacy against various neurological complications.
Описание: As part of the Oxford American Pain Library, this practical handbook is designed to serve as an authoritative resource on diagnosing and treating back and neck pain. Co-authored by two primary care physicians and a nurse practitioner with extensive expertise in pain medicine and management, it is tailored to the needs of busy health care professionalsand focuses on essential clinical information.
Автор: Jude Hemanth D. Название: Handbook of Decision Support Systems for Neurological Disorders ISBN: 0128222719 ISBN-13(EAN): 9780128222713 Издательство: Elsevier Science Рейтинг: Цена: 21896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Handbook of Decision Support Systems for Neurological Disorders provides readers with complete coverage of advanced computer-aided diagnosis systems for neurological disorders. While computer-aided decision support systems for different medical imaging modalities are available, this is the first book to solely concentrate on decision support systems for neurological disorders. Due to the increase in the prevalence of diseases such as Alzheimer, Parkinson's and Dementia, this book will have significant importance in the medical field. Topics discussed include recent computational approaches, different types of neurological disorders, deep convolution neural networks, generative adversarial networks, auto encoders, recurrent neural networks, and modified/hybrid artificial neural networks.
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