EEG Brain Signal Classification for Epileptic Seizure Disorder Detection

Book EEG Brain Signal Classification for Epileptic Seizure Disorder Detection Cover

Read or download book entitled EEG Brain Signal Classification for Epileptic Seizure Disorder Detection written by Sandeep Kumar Satapathy and published by Academic Press in PDF, EPUB and Kindle Format. Click Get This Book button to download or read online books. Join over 650.000 happy Readers and READ as many books as you like. We cannot guarantee that EEG Brain Signal Classification for Epileptic Seizure Disorder Detection book is available in the library.

  • Publisher : Academic Press
  • Release : 10 February 2019
  • ISBN : 9780128174272
  • Page : 134 pages
  • Rating : 4.5/5 from 103 voters

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EEG Brain Signal Classification for Epileptic Seizure Disorder Detection provides the knowledge necessary to classify EEG brain signals to detect epileptic seizures using machine learning techniques. Chapters present an overview of machine learning techniques and the tools available, discuss previous studies, present empirical studies on the performance of the NN and SVM classifiers, discuss RBF neural networks trained with an improved PSO algorithm for epilepsy identification, and cover ABC algorithm optimized RBFNN for classification of EEG signal. Final chapter present future developments in the field. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need the most recent and promising automated techniques for EEG classification. Explores machine learning techniques that have been modified and validated for the purpose of EEG signal classification using Discrete Wavelet Transform for the identification of epileptic seizures Encompasses machine learning techniques, providing an easily understood resource for both non-specialized readers and biomedical researchers Provides a number of experimental analyses, with their results discussed and appropriately validated

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EEG Brain Signal Classification for Epileptic Seizure Disorder Detection

EEG Brain Signal Classification for Epileptic Seizure Disorder Detection
  • Author : Sandeep Kumar Satapathy,Satchidananda Dehuri,Alok Kumar Jagadev,Shruti Mishra
  • Publisher : Academic Press
  • Release Date : 2019-02-10
  • ISBN : 9780128174272
GET THIS BOOKEEG Brain Signal Classification for Epileptic Seizure Disorder Detection

EEG Brain Signal Classification for Epileptic Seizure Disorder Detection provides the knowledge necessary to classify EEG brain signals to detect epileptic seizures using machine learning techniques. Chapters present an overview of machine learning techniques and the tools available, discuss previous studies, present empirical studies on the performance of the NN and SVM classifiers, discuss RBF neural networks trained with an improved PSO algorithm for epilepsy identification, and cover ABC algorithm optimized RBFNN for classification of EEG signal. Final chapter present

Brain Seizure Detection and Classification Using EEG Signals

Brain Seizure Detection and Classification Using EEG Signals
  • Author : Varsha K. Harpale,Vinayak Bairagi
  • Publisher : Academic Press
  • Release Date : 2021-09-09
  • ISBN : 9780323911214
GET THIS BOOKBrain Seizure Detection and Classification Using EEG Signals

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).

EEG Signal Analysis and Classification

EEG Signal Analysis and Classification
  • Author : Siuly Siuly,Yan Li,Yanchun Zhang
  • Publisher : Springer
  • Release Date : 2017-01-03
  • ISBN : 9783319476537
GET THIS BOOKEEG Signal Analysis and Classification

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

Data Mining and Machine Learning Applications

Data Mining and Machine Learning Applications
  • Author : Rohit Raja,Kapil Kumar Nagwanshi,Sandeep Kumar,K. Ramya Laxmi
  • Publisher : Wiley-Scrivener
  • Release Date : 2022-03-15
  • ISBN : 1119791782
GET THIS BOOKData Mining and Machine Learning Applications

DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data

EEG Signal Processing

EEG Signal Processing
  • Author : Saeid Sanei,Jonathon A. Chambers
  • Publisher : John Wiley & Sons
  • Release Date : 2013-05-28
  • ISBN : 9781118691236
GET THIS BOOKEEG Signal Processing

Electroencephalograms (EEGs) are becoming increasingly important measurements of brain activity and they have great potential for the diagnosis and treatment of mental and brain diseases and abnormalities. With appropriate interpretation methods they are emerging as a key methodology to satisfy the increasing global demand for more affordable and effective clinical and healthcare services. Developing and understanding advanced signal processing techniques for the analysis of EEG signals is crucial in the area of biomedical research. This book focuses on these techniques,

Early Detection of Neurological Disorders Using Machine Learning Systems

Early Detection of Neurological Disorders Using Machine Learning Systems
  • Author : Paul, Sudip,Bhattacharya, Pallab,Bit, Arindam
  • Publisher : IGI Global
  • Release Date : 2019-06-28
  • ISBN : 9781522585688
GET THIS BOOKEarly Detection of Neurological Disorders Using Machine Learning Systems

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

KNN Classifier and K-Means Clustering for Robust Classification of Epilepsy from EEG Signals. A Detailed Analysis

KNN Classifier and K-Means Clustering for Robust Classification of Epilepsy from EEG Signals. A Detailed Analysis
  • Author : Harikumar Rajaguru,Sunil Kumar Prabhakar
  • Publisher : Anchor Academic Publishing
  • Release Date : 2017-05
  • ISBN : 9783960671404
GET THIS BOOKKNN Classifier and K-Means Clustering for Robust Classification of Epilepsy from EEG Signals. A Detailed Analysis

Epilepsy is a chronic disorder, the hallmark of which is recurrent, unprovoked seizures. Many people with epilepsy have more than one type of seizures and may have other symptoms of neurological problems as well. Epilepsy is caused due to sudden recurrent firing of the neurons in the brain. The symptoms are convulsions, dizziness and confusion. One out of every hundred persons experiences a seizure at some time in their lives. It may be confused with other events like strokes or

Comparison of Three Nonlinear Seizure Prediction Methods by Means of the Seizure Prediction Characteristic

Comparison of Three Nonlinear Seizure Prediction Methods by Means of the Seizure Prediction Characteristic
  • Author : Anonim
  • Publisher : Unknown
  • Release Date : 2003
  • ISBN : 3887225945
GET THIS BOOKComparison of Three Nonlinear Seizure Prediction Methods by Means of the Seizure Prediction Characteristic

Digital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine

Digital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine
  • Author : Lotfi Chaari
  • Publisher : Springer
  • Release Date : 2019-07-10
  • ISBN : 9783030118006
GET THIS BOOKDigital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine

This collection, entitled Digital Health for Predictive, Preventive, Personalized and Participatory Medicine contains the proceedings of the first International conference on digital healthtechnologies (ICDHT 2018). Ten recent contributions in the fields of Artificial Intelligence (AI) and machine learning, Internet of Things (IoT) and data analysis, all applied to digital health. This collection enables researchers to learn about recent advances in the above mentioned fields. It brings a technological viewpoint of P4 medicine. Readers will discover how advanced Information Technology (IT) tools

Intelligent Computing & Optimization

Intelligent Computing & Optimization
  • Author : Ivan Zelinka
  • Publisher : Springer Nature
  • Release Date : 2022
  • ISBN : 9783030932473
GET THIS BOOKIntelligent Computing & Optimization

This book of Springer Nature is another proof of Springers outstanding and greatness on the lively interface of Smart Optimization, Computational Science, Human Intelligence and Machine Learning! It is a Master Piece of what our community of Academics and Experts can provide when an Interdisciplinary Approach of Joint, Mutual and Deep Learning is supported by Modern Mathematics and Experience of the World-Leader Springer Nature! Fourth edition of International Conference on Intelligent Computing and Optimization took place at December 3031, 2021, via ZOOM.

Comprehensive Analysis of Extreme Learning Machine and Continuous Genetic Algorithm for Robust Classification of Epilepsy from EEG Signals

Comprehensive Analysis of Extreme Learning Machine and Continuous Genetic Algorithm for Robust Classification of Epilepsy from EEG Signals
  • Author : Harikumar Rajaguru,Sunil Kumar Prabhakar
  • Publisher : Anchor Academic Publishing
  • Release Date : 2017-01
  • ISBN : 9783960670995
GET THIS BOOKComprehensive Analysis of Extreme Learning Machine and Continuous Genetic Algorithm for Robust Classification of Epilepsy from EEG Signals

Epilepsy is a common and diverse set of chronic neurological disorders characterized by seizures. It is a paroxysmal behavioral spell generally caused by an excessive disorderly discharge of cortical nerve cells of the brain. Epilepsy is marked by the term “epileptic seizures”. Epileptic seizures result from abnormal, excessive or hyper-synchronous neuronal activity in the brain. About 50 million people worldwide have epilepsy, and nearly 80% of epilepsy occurs in developing countries. The most common way to interfere with epilepsy is to analyse

Atlas of EEG, Seizure Semiology, and Management

Atlas of EEG, Seizure Semiology, and Management
  • Author : Karl E. Misulis
  • Publisher : Oxford University Press
  • Release Date : 2013-12
  • ISBN : 9780199985906
GET THIS BOOKAtlas of EEG, Seizure Semiology, and Management

This resource is an illustrated guide to the performance and interpretation of EEG and management of epilepsy. This second edition has been thoroughly revised and updated, and features hundreds of detailed EEGs covering the science in extensive scope and detail, beginning with basic electronics and physiology, followed by EEG interpretation, epilepsy diagnosis, and ultimately epilepsy management. It also includes all basic classifications and definitions of seizures and epilepsy.

Advanced Deep-Transfer-Leveraged Studies on Brain-Computer Interfacing

Advanced Deep-Transfer-Leveraged Studies on Brain-Computer Interfacing
  • Author : Yizhang Jiang,Yu-Dong Zhang,Mohammad Khosravi
  • Publisher : Frontiers Media SA
  • Release Date : 2021-10-13
  • ISBN : 9782889714681
GET THIS BOOKAdvanced Deep-Transfer-Leveraged Studies on Brain-Computer Interfacing

Seizure Prediction in Epilepsy

Seizure Prediction in Epilepsy
  • Author : Björn Schelter,Jens Timmer,Andreas Schulze-Bonhage
  • Publisher : John Wiley & Sons
  • Release Date : 2008-11-21
  • ISBN : 9783527625208
GET THIS BOOKSeizure Prediction in Epilepsy

Comprising some 30 contributions, experts from around the world present and discuss recent advances related to seizure prediction in epilepsy. The book covers an extraordinarily broad spectrum, starting from modeling epilepsy in single cells or networks of a few cells to precisely-tailored seizure prediction techniques as applied to human data. This unique overview of our current level of knowledge and future perspectives provides theoreticians as well as practitioners, newcomers and experts with an up-to-date survey of developments in this important field

Transfer and Multitask Learning Methods for Improving Brain Signal Analysis

Transfer and Multitask Learning Methods for Improving Brain Signal Analysis
  • Author : Boyu Wang
  • Publisher : Unknown
  • Release Date : 2017
  • ISBN : OCLC:979422411
GET THIS BOOKTransfer and Multitask Learning Methods for Improving Brain Signal Analysis

"The human brain is one of the most complicated biological systems in the world. The brain activities measured by various signals such as electroencephalogram (EEG), electrocorticogram (ECoG), and functional magnetic resonance imaging (fMRI) provide avenues that can help understand the underlying mechanisms of the brain as well as diagnosis brain disorders and the related diseases. However, without the proper techniques to analyze the brain signals, they are of limited value. In this thesis, we formulate the brain signal analysis as