Brain Seizure Detection And Classification Using Eeg Signals

Author : Varsha K. Harpale,Vinayak Bairagi
Publisher : Academic Press
Page : 176 pages
File Size : 46,7 Mb
Release : 2021-09-09
Category : Science
ISBN : 9780323911214

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Brain Seizure Detection and Classification Using EEG Signals by Varsha K. Harpale,Vinayak Bairagi Pdf

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 : Sandeep Kumar Satapathy,Satchidananda Dehuri,Alok Kumar Jagadev,Shruti Mishra
Publisher : Academic Press
Page : 134 pages
File Size : 43,8 Mb
Release : 2019-02-10
Category : Medical
ISBN : 9780128174272

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EEG Brain Signal Classification for Epileptic Seizure Disorder Detection by Sandeep Kumar Satapathy,Satchidananda Dehuri,Alok Kumar Jagadev,Shruti Mishra Pdf

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

Author : Siuly Siuly,Yan Li,Yanchun Zhang
Publisher : Springer
Page : 256 pages
File Size : 51,9 Mb
Release : 2017-01-03
Category : Technology & Engineering
ISBN : 9783319476537

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EEG Signal Analysis and Classification by Siuly Siuly,Yan Li,Yanchun Zhang Pdf

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 : Rohit Raja,Kapil Kumar Nagwanshi,Sandeep Kumar,K. Ramya Laxmi
Publisher : John Wiley & Sons
Page : 500 pages
File Size : 40,7 Mb
Release : 2022-01-26
Category : Computers
ISBN : 9781119792505

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Data Mining and Machine Learning Applications by Rohit Raja,Kapil Kumar Nagwanshi,Sandeep Kumar,K. Ramya Laxmi Pdf

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 analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.

Author : Andrea Varsavsky,Iven Mareels,Mark Cook
Publisher : CRC Press
Page : 376 pages
File Size : 41,8 Mb
Release : 2016-04-19
Category : Medical
ISBN : 9781000218923

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Epileptic Seizures and the EEG by Andrea Varsavsky,Iven Mareels,Mark Cook Pdf

A study of epilepsy from an engineering perspective, this volume begins by summarizing the physiology and the fundamental ideas behind the measurement, analysis and modeling of the epileptic brain. It introduces the EEG and provides an explanation of the type of brain activity likely to register in EEG measurements, offering an overview of how these EEG records are and have been analyzed in the past. The book focuses on the problem of seizure detection and surveys the physiologically based dynamic models of brain activity. Finally, it addresses the fundamental question: can seizures be predicted? Based on the authors' extensive research, the book concludes by exploring a range of future possibilities in seizure prediction.

Author : Saeid Sanei,Jonathon A. Chambers
Publisher : John Wiley & Sons
Page : 312 pages
File Size : 51,5 Mb
Release : 2013-05-28
Category : Science
ISBN : 9781118691236

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EEG Signal Processing by Saeid Sanei,Jonathon A. Chambers Pdf

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, providing expansive coverage of algorithms and tools from the field of digital signal processing. It discusses their applications to medical data, using graphs and topographic images to show simulation results that assess the efficacy of the methods. Additionally, expect to find: explanations of the significance of EEG signal analysis and processing (with examples) and a useful theoretical and mathematical background for the analysis and processing of EEG signals; an exploration of normal and abnormal EEGs, neurological symptoms and diagnostic information, and representations of the EEGs; reviews of theoretical approaches in EEG modelling, such as restoration, enhancement, segmentation, and the removal of different internal and external artefacts from the EEG and ERP (event-related potential) signals; coverage of major abnormalities such as seizure, and mental illnesses such as dementia, schizophrenia, and Alzheimer’s disease, together with their mathematical interpretations from the EEG and ERP signals and sleep phenomenon; descriptions of nonlinear and adaptive digital signal processing techniques for abnormality detection, source localization and brain-computer interfacing using multi-channel EEG data with emphasis on non-invasive techniques, together with future topics for research in the area of EEG signal processing. The information within EEG Signal Processing has the potential to enhance the clinically-related information within EEG signals, thereby aiding physicians and ultimately providing more cost effective, efficient diagnostic tools. It will be beneficial to psychiatrists, neurophysiologists, engineers, and students or researchers in neurosciences. Undergraduate and postgraduate biomedical engineering students and postgraduate epileptology students will also find it a helpful reference.

Author : Brijesh Verma,Ligang Zhang,David Stockwell
Publisher : Springer
Page : 189 pages
File Size : 46,8 Mb
Release : 2017-04-28
Category : Technology & Engineering
ISBN : 9789811045394

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Roadside Video Data Analysis by Brijesh Verma,Ligang Zhang,David Stockwell Pdf

This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment.

Author : Narayan Panigrahi,Saraju P. Mohanty
Publisher : CRC Press
Page : 216 pages
File Size : 45,5 Mb
Release : 2022
Category : Computers
ISBN : 1003241387

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Brain Computer Interface by Narayan Panigrahi,Saraju P. Mohanty Pdf

Brain Computer Interface: EEG Signal Processing discusses electroencephalogram (EEG) signal processing using effective methodology and algorithms. This book provides a basic introduction to EEG and a classification of different components present in EEG. It also helps the reader to understand the scope of processing EEG signals and their associated applications. Further, it covers specific aspects such as epilepsy detection; exploitation of P300 for various applications; design of an EEG acquisition system; and detection of saccade, fix, and blink from EEG and EOG data. Key Features: Explains the basis of brain computer interface and how it can be established using different EEG signal characteristics Covers the detailed classification of different types of EEG signals with respect to their physical characteristics Explains detection and diagnosis of epileptic seizures from the EEG data of a subject Reviews the design and development of a low-cost and robust EEG acquisition system Provides mathematical analysis of EEGs, including MATLAB® codes for students to experiment with EEG data This book is aimed at graduate students and researchers in biomedical, electrical, electronics, communication engineering, healthcare, and cyber physical systems.

Author : Li Hu,Zhiguo Zhang
Publisher : Springer Nature
Page : 437 pages
File Size : 53,8 Mb
Release : 2019-10-12
Category : Medical
ISBN : 9789811391132

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EEG Signal Processing and Feature Extraction by Li Hu,Zhiguo Zhang Pdf

This book presents the conceptual and mathematical basis and the implementation of both electroencephalogram (EEG) and EEG signal processing in a comprehensive, simple, and easy-to-understand manner. EEG records the electrical activity generated by the firing of neurons within human brain at the scalp. They are widely used in clinical neuroscience, psychology, and neural engineering, and a series of EEG signal-processing techniques have been developed. Intended for cognitive neuroscientists, psychologists and other interested readers, the book discusses a range of current mainstream EEG signal-processing and feature-extraction techniques in depth, and includes chapters on the principles and implementation strategies.

Author : Paul, Sudip,Bhattacharya, Pallab,Bit, Arindam
Publisher : IGI Global
Page : 376 pages
File Size : 51,6 Mb
Release : 2019-06-28
Category : Medical
ISBN : 9781522585688

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Early Detection of Neurological Disorders Using Machine Learning Systems by Paul, Sudip,Bhattacharya, Pallab,Bit, Arindam Pdf

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 : Harikumar Rajaguru,Sunil Kumar Prabhakar
Publisher : Anchor Academic Publishing
Page : 57 pages
File Size : 42,8 Mb
Release : 2017-05
Category : Computers
ISBN : 9783960671404

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KNN Classifier and K-Means Clustering for Robust Classification of Epilepsy from EEG Signals. A Detailed Analysis by Harikumar Rajaguru,Sunil Kumar Prabhakar Pdf

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 migraines. Unfortunately, the occurrence of an epileptic seizure seems unpredictable and its process still is hardly understood. In India, the number of persons suffering from epilepsy is increasing every year. The complexity involved in the diagnosis and therapy has to be cost effective. In this project, the authors applied an algorithm which is used for a classification of the risk level of epilepsy in epileptic patients from Electroencephalogram (EEG) signals. Dimensionality reduction is done on the EEG dataset by applying Power Spectral density. The KNN Classifier and K-Means clustering is implemented on these spectral values to epilepsy risk level detection. The Performance Index (PI) and Quality Value (QV) are calculated for the above methods. A group of twenty patients with known epilepsy findings are used in this study.

Author : Anonim
Publisher : Unknown
Page : 99 pages
File Size : 45,6 Mb
Release : 2019
Category : Medical informatics
ISBN : 3030118010

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Digital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine by Anonim Pdf

This collection, entitled #x1B;(S0#x1B;(B Digital Health for Predictive, Preventive, Personalized and Participatory Medicine#x1B;(S1#x1B;(B contains the proceedings of the first International conference on digital health technologies (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 can be used for healthcare. For instance, the use of connected objects to monitor physiological parameters is discussed. Moreover, even if compressed sensing is nowadays a common acquisition technique, its use for IoT is presented in this collection through one of the pioneer works in the field. In addition, the use of AI for epileptic seizure detection is also discussed as being one of the major concerns of predictive medicine both in industrialized and low-income countries. This work is edited by Prof. Lotfi Chaari, professor at the University of Sfax, and previously at the University of Toulouse. This work comes after more than ten years of expertise in the biomedical signal and image processing field.

Author : Nitish V. Thakor
Publisher : Springer Nature
Page : 3686 pages
File Size : 49,5 Mb
Release : 2023-02-02
Category : Technology & Engineering
ISBN : 9789811655401

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Handbook of Neuroengineering by Nitish V. Thakor Pdf

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 : Anonim
Publisher : Unknown
Page : 20 pages
File Size : 47,5 Mb
Release : 2003
Category : Electronic
ISBN : 3887225945

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

Author : Kusum Deep,Atulya Nagar,Millie Pant,Jagdish Chand Bansal
Publisher : Springer Science & Business Media
Page : 1059 pages
File Size : 49,7 Mb
Release : 2012-04-13
Category : Technology & Engineering
ISBN : 9788132204916

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Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011 by Kusum Deep,Atulya Nagar,Millie Pant,Jagdish Chand Bansal Pdf

The objective is to provide the latest developments in the area of soft computing. These are the cutting edge technologies that have immense application in various fields. All the papers will undergo the peer review process to maintain the quality of work.