EEG Brain Signal Classification for Epileptic Seizure Disorder Detection

• Author : Sandeep Kumar Satapathy,Satchidananda Dehuri,Alok Kumar Jagadev,Shruti Mishra
• Publisher : Academic Press
• Release : 10 February 2019

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

• Author : Varsha K. Harpale,Vinayak Bairagi
• Publisher : Academic Press
• Release : 09 September 2021

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).

• Author : Saeid Sanei,Jonathon A. Chambers
• Publisher : John Wiley & Sons
• Release : 28 May 2013

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,

• Author : Harikumar Rajaguru,Sunil Kumar Prabhakar
• Publisher : Anchor Academic Publishing
• Release : 01 January 2017

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

• Author : Boyu Wang
• Publisher : Unknown
• Release : 16 May 2022

"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

• Author : Sasikumar Gurumoorthy,Naresh Babu Muppalaneni,Xiao-Zhi Gao
• Publisher : Springer
• Release : 05 September 2017

This book highlights a new biomedical signal processing method of extracting a specific underlying signal from possibly noisy multi-channel recordings, and shows that the method is suitable for extracting independent components from the measured electroencephalogram (EEG) signal. The system efficiently extracts memory spindles and is also effective in Alzheimer seizures. Current developments in computer hardware and signal processing have made it possible for EEG signals or “brain waves” to communicate between humans and computers – an area that can be extended

• Author : Mintaze Kerem Günel
• Publisher : BoD – Books on Demand
• Release : 15 September 2011

Epilepsy is one of the most common neurological disorders, with a prevalence of 4-10/1000. The book contains the practical methods to approaching the classification and diagnosis of epilepsy, and provides information on management. Epilepsy is a comprehensive book which guides the reader through all aspects of epilepsy, both practical and academic, covering all aspects of diagnosis and management of children with epilepsy in a clear, concise, and practical fashion. The book is organized so that it can either be read

• Author : Saeid Sanei,Jonathon A. Chambers
• Publisher : John Wiley & Sons
• Release : 23 September 2021

EEG Signal Processing and Machine Learning Explore cutting edge techniques at the forefront of electroencephalogram research and artificial intelligence from leading voices in the field The newly revised Second Edition of EEG Signal Processing and Machine Learning delivers an inclusive and thorough exploration of new techniques and outcomes in electroencephalogram (EEG) research in the areas of analysis, processing, and decision making about a variety of brain states, abnormalities, and disorders using advanced signal processing and machine learning techniques. The book

• Author : Muhammad Aamir Cheema,Wenjie Zhang,Lijun Chang
• Publisher : Springer
• Release : 20 September 2016

This book constitutes the refereed proceedings of the 27th Australasian Database Conference, ADC 2016, held in Sydney, NSW, Australia, in September 2016. The 33 full papers presented together with 11 demo papers were carefully reviewed and selected from 55 submissions. The mission of ADC is to share novel research solutions to problems of today’s information society that fulfill the needs of heterogeneous applications and environments and to identify new issues and directions for future research. The topics of the presented papers are related to

• Author : Varun Bajaj,G. R. Sinha
• Publisher : Academic Press
• Release : 08 February 2022

Artificial Intelligence-Based Brain Computer Interface provides concepts of AI for modelling of non-invasive modalities of medical signals such as EEG, MRI, and FMRI. These modalities and their AI-based analysis are employed in BCI and related applications. This can help to improve the healthcare system through detection, identification, predication, analysis and classification of disease, management of chronic conditions, and delivery of health services. Artificial Intelligence-Based Brain Computer Interface emphasizes the real challenges in non-invasive input due to the complex nature of

• Author : Derong Liu,Shengli Xie,Yuanqing Li,Dongbin Zhao,El-Sayed M. El-Alfy
• Publisher : Springer
• Release : 07 November 2017

The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constitues the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017. The 563 full papers presented were carefully reviewed and selected from 856 submissions. The 6 volumes are organized in topical sections on Machine Learning, Reinforcement Learning, Big Data Analysis, Deep Learning, Brain-Computer Interface, Computational Finance, Computer Vision, Neurodynamics, Sensory Perception and Decision Making, Computational Intelligence, Neural Data Analysis, Biomedical Engineering, Emotion and Bayesian

• Author : Farshad Firouzi,Krishnendu Chakrabarty,Sani Nassif
• Publisher : Springer Nature
• Release : 21 January 2020

This holistic book is an invaluable reference for addressing various practical challenges in architecting and engineering Intelligent IoT and eHealth solutions for industry practitioners, academic and researchers, as well as for engineers involved in product development. The first part provides a comprehensive guide to fundamentals, applications, challenges, technical and economic benefits, and promises of the Internet of Things using examples of real-world applications. It also addresses all important aspects of designing and engineering cutting-edge IoT solutions using a cross-layer approach

• Author : Kumar, M. Rajesh,Kumar, Ranjeet,Vaithiyanathan, D.
• Publisher : IGI Global
• Release : 25 June 2021

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

• Author : João Manuel R. S. Tavares,Satyajit Chakrabarti,Abhishek Bhattacharya,Sujata Ghatak
• Publisher : Springer Nature
• Release : 04 May 2021

This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2020) held at the University of Engineering & Management, Kolkata, India, during July 2020. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, and case studies related to all the areas of data mining, machine learning, Internet of things (IoT), and information security.

• Author : Sudip Paul,Dinesh Bhatia
• Publisher : Academic Press
• Release : 14 January 2020

Smart Healthcare for Disease Diagnosis and Prevention focuses on the advancement in healthcare technology to improve human health at all levels using smart technologies. It covers all necessary topics from basic concepts (such as signal and image processing) to advanced knowledge on topics such as tissue engineering, virtual and intelligent instrumentation (or VLSI) and Embedded Systems. This book can be used to guide students and young researchers, providing basic knowledge on signal/image processing and smart technologies. Users will find