Author : Chrysostomos P. Panayiotopoulos
Publisher : Springer
Page : 570 pages
File Size : 43,19 MB
Release : 2005
Category : Medical
ISBN :
This book gives an exhaustive account of the classification and management of epileptic disorders. It provides clear didactic guidance on the diagnosis and treatment of epileptic syndromes and seizures through thirteen chapters, complemented by a pharmacopoeia and CD ROM of video-EEGs.
Author : Varsha K. Harpale
Publisher : Academic Press
Page : 178 pages
File Size : 19,65 MB
Release : 2021-09-09
Category : Science
ISBN : 0323911218
Brain Seizure Detection and Classification Using Electroencephalographic Signals presents EEG signal processing and analysis with high performance feature extraction. The book covers the feature selection method based on One-way ANOVA, along with high performance machine learning classifiers for the classification of EEG signals in normal and epileptic EEG signals. In addition, the authors also present new methods of feature extraction, including Singular Spectrum-Empirical Wavelet Transform (SSEWT) for improved classification of seizures in significant seizure-types, specifically epileptic and Non-Epileptic Seizures (NES). The performance of the system is compared with existing methods of feature extraction using Wavelet Transform (WT) and Empirical Wavelet Transform (EWT). The book's objective is to analyze the EEG signals to observe abnormalities of brain activities called epileptic seizure. Seizure is a neurological disorder in which too many neurons are excited at the same time and are triggered by brain injury or by chemical imbalance. - Presents EEG signal processing and analysis concepts with high performance feature extraction - Discusses recent trends in seizure detection, prediction and classification methodologies - Helps classify epileptic and non-epileptic seizures where misdiagnosis may lead to the unnecessary use of antiepileptic medication - Provides new guidance and technical discussions on feature-extraction methods and feature selection methods based on One-way ANOVA, along with high performance machine learning classifiers for classification of EEG signals in normal and epileptic EEG signals, and new methods of feature extraction developed by the authors, including Singular Spectrum-Empirical Wavelet
Author : Siuly Siuly
Publisher : Springer
Page : 257 pages
File Size : 26,80 MB
Release : 2017-01-03
Category : Technology & Engineering
ISBN : 331947653X
This book presents advanced methodologies in two areas related to electroencephalogram (EEG) signals: detection of epileptic seizures and identification of mental states in brain computer interface (BCI) systems. The proposed methods enable the extraction of this vital information from EEG signals in order to accurately detect abnormalities revealed by the EEG. New methods will relieve the time-consuming and error-prone practices that are currently in use. Common signal processing methodologies include wavelet transformation and Fourier transformation, but these methods are not capable of managing the size of EEG data. Addressing the issue, this book examines new EEG signal analysis approaches with a combination of statistical techniques (e.g. random sampling, optimum allocation) and machine learning methods. The developed methods provide better results than the existing methods. The book also offers applications of the developed methodologies that have been tested on several real-time benchmark databases. This book concludes with thoughts on the future of the field and anticipated research challenges. It gives new direction to the field of analysis and classification of EEG signals through these more efficient methodologies. Researchers and experts will benefit from its suggested improvements to the current computer-aided based diagnostic systems for the precise analysis and management of EEG signals. /div
Author : Dilip Singh Sisodia
Publisher : Medical Information Science Reference
Page : 300 pages
File Size : 35,29 MB
Release : 2020
Category :
ISBN : 9781799821205
"This book explores the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in the design, implementation, and optimization of challenging healthcare engineering solutions"--
Author : Iyad Obeid
Publisher : Springer Nature
Page : 287 pages
File Size : 45,14 MB
Release : 2020-03-16
Category : Technology & Engineering
ISBN : 3030368440
This book covers emerging trends in signal processing research and biomedical engineering, exploring the ways in which signal processing plays a vital role in applications ranging from medical electronics to data mining of electronic medical records. Topics covered include statistical modeling of electroencephalograph data for predicting or detecting seizure, stroke, or Parkinson’s; machine learning methods and their application to biomedical problems, which is often poorly understood, even within the scientific community; signal analysis; medical imaging; and machine learning, data mining, and classification. The book features tutorials and examples of successful applications that will appeal to a wide range of professionals and researchers interested in applications of signal processing, medicine, and biology.
Author : Nitish V. Thakor
Publisher : Springer Nature
Page : 3686 pages
File Size : 11,83 MB
Release : 2023-02-02
Category : Technology & Engineering
ISBN : 9811655405
This Handbook serves as an authoritative reference book in the field of Neuroengineering. Neuroengineering is a very exciting field that is rapidly getting established as core subject matter for research and education. The Neuroengineering field has also produced an impressive array of industry products and clinical applications. It also serves as a reference book for graduate students, research scholars and teachers. Selected sections or a compendium of chapters may be used as “reference book” for a one or two semester graduate course in Biomedical Engineering. Some academicians will construct a “textbook” out of selected sections or chapters. The Handbook is also meant as a state-of-the-art volume for researchers. Due to its comprehensive coverage, researchers in one field covered by a certain section of the Handbook would find other sections valuable sources of cross-reference for information and fertilization of interdisciplinary ideas. Industry researchers as well as clinicians using neurotechnologies will find the Handbook a single source for foundation and state-of-the-art applications in the field of Neuroengineering. Regulatory agencies, entrepreneurs, investors and legal experts can use the Handbook as a reference for their professional work as well.
Author : Kumar, M. Rajesh
Publisher : IGI Global
Page : 290 pages
File Size : 26,7 MB
Release : 2021-06-25
Category : Health & Fitness
ISBN : 1799880192
There are more than 80 different sleep disorders including insomnia, sleep apnea, restless leg syndrome, hypersomnia, circadian rhythm disorders, and parasomnia. Good sleep is necessary for optimal health and can affect hormone levels and weight. The use of artificial intelligence (AI) and biomedical signals and images can help in healthcare diagnostics that are related to these and other sleep disorders. Advancing the Investigation and Treatment of Sleep Disorders Using AI presents an overview of sleep disorders based on machine intelligence methods in order to learn and explore the latest advancements, developments, methods, systems, futuristic approaches, and algorithms towards sleep disorders and to address their challenges. This book also discusses recent and future advancements in various feature extraction techniques and machine learning methods. Covering topics such as biomedical signal processing, augmented reality for clinical investigation, and sleep disorder detection, this book is essential for sleep medicine practitioners, clinical psychologists, psychiatrists, medical technologists, doctors, IT specialists, biomedical engineers, researchers, graduate students, and academicians.
Author : Paul, Sudip
Publisher : IGI Global
Page : 392 pages
File Size : 36,85 MB
Release : 2019-06-28
Category : Medical
ISBN : 1522585680
While doctors and physicians are more than capable of detecting diseases of the brain, the most agile human mind cannot compete with the processing power of modern technology. Utilizing algorithmic systems in healthcare in this way may provide a way to treat neurological diseases before they happen. Early Detection of Neurological Disorders Using Machine Learning Systems provides innovative insights into implementing smart systems to detect neurological diseases at a faster rate than by normal means. The topics included in this book are artificial intelligence, data analysis, and biomedical informatics. It is designed for clinicians, doctors, neurologists, physiotherapists, neurorehabilitation specialists, scholars, academics, and students interested in topics centered on biomedical engineering, bio-electronics, medical electronics, physiology, neurosciences, life sciences, and physics.
Author : Gonzalo Alarcón
Publisher : Cambridge University Press
Page : 641 pages
File Size : 49,17 MB
Release : 2012-04-26
Category : Medical
ISBN : 0521691583
Covers all aspects of epilepsy, from basic mechanisms to diagnosis and management, as well as legal and social considerations.
Author : Poonam Bansal
Publisher : Springer Nature
Page : 604 pages
File Size : 49,63 MB
Release : 2020-07-01
Category : Technology & Engineering
ISBN : 9811549923
This book gathers high-quality papers presented at the International Conference on Artificial Intelligence and Applications (ICAIA 2020), held at Maharaja Surajmal Institute of Technology, New Delhi, India, on 6–7 February 2020. The book covers areas such as artificial neural networks, fuzzy systems, computational optimization technologies and machine learning.
