ICA-based Epileptic Seizure Detection Using ECoG Signals
Author | : Yu Han |
Publisher | : |
Total Pages | : 100 |
Release | : 2011 |
Genre | : |
ISBN | : |
Download ICA-based Epileptic Seizure Detection Using ECoG Signals Book in PDF, ePub and Kindle
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Ica Based Epileptic Seizure Detection Using Ecog Signals PDF full book. Access full book title Ica Based Epileptic Seizure Detection Using Ecog Signals.
Author | : Yu Han |
Publisher | : |
Total Pages | : 100 |
Release | : 2011 |
Genre | : |
ISBN | : |
Author | : Varsha K. Harpale |
Publisher | : Academic Press |
Total Pages | : 176 |
Release | : 2021-09-09 |
Genre | : 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 | : 張涵彥 |
Publisher | : |
Total Pages | : 158 |
Release | : 2010 |
Genre | : |
ISBN | : |
Author | : Ratnaprabha Ravindra Borhade |
Publisher | : |
Total Pages | : 0 |
Release | : 2024-10 |
Genre | : Medical |
ISBN | : 9781032725932 |
"This book presents an innovative method of EEG-based feature extraction and classification of seizures using EEG signals. It describes the methodology required for EEG analysis, seizure detection, seizure prediction and seizure classification. It contains a compilation of all techniques used in the literature and emphasises on newly proposed techniques. The book concentrates on a brief discussion of existing methods for epileptic seizure diagnosis and prediction and introduces new efficient methods specifically for seizure prediction. Focuses on the mathematical models and machine learning algorithms from a perspective of clinical deployment of EEG-based Epileptic Seizure Prediction Discusses recent trends in seizure detection, prediction and classification methodologies Provides engineering solutions to severity or risk analysis of detected seizures at remote places Presents wearable solutions to seizure prediction Includes details of the use of deep learning for Epileptic Seizure Prediction using EEG This book acts as a reference for academicians and professionals who are working in the field of Computational Biomedical Engineering and are interested in the domain of EEG-based disease prediction"--
Author | : Manoj Shrikrishna Nagmode |
Publisher | : |
Total Pages | : 0 |
Release | : 2024-12-10 |
Genre | : |
ISBN | : 9781032714394 |
Author | : Donald L. Schomer |
Publisher | : Lippincott Williams & Wilkins |
Total Pages | : 1308 |
Release | : 2012-10-18 |
Genre | : Medical |
ISBN | : 1451153155 |
The leading reference on electroencephalography since 1982, Niedermeyer's Electroencephalography is now in its thoroughly updated Sixth Edition. An international group of experts provides comprehensive coverage of the neurophysiologic and technical aspects of EEG, evoked potentials, and magnetoencephalography, as well as the clinical applications of these studies in neonates, infants, children, adults, and older adults. This edition's new lead editor, Donald Schomer, MD, has updated the technical information and added a major new chapter on artifacts. Other highlights include complete coverage of EEG in the intensive care unit and new chapters on integrating other recording devices with EEG; transcranial electrical and magnetic stimulation; EEG/TMS in evaluation of cognitive and mood disorders; and sleep in premature infants, children and adolescents, and the elderly. A companion website includes fully searchable text and image bank.
Author | : Edward F. Chang |
Publisher | : Elsevier Health Sciences |
Total Pages | : 139 |
Release | : 2011-10-28 |
Genre | : Medical |
ISBN | : 1455712140 |
In this issue of Neurosurgery Clinics, Drs. Chang and Barbaro provide a thorough look at epilepsy, with sections focusing on devices in epilepsy surgery, open loop systems, closed loop systems, and non-stimulation. Topics in this issue include history and overview of stimulation for epilepsy, trigeminal nerve stimulation, anterior thalamus DBS, hippocampal stimulation, neuropace RNS, seizure detection/prediction algorithms, cooling, seizure prediction and its applications, stimulation paradigms, and experimental stimulation.
Author | : Saeid Sanei |
Publisher | : John Wiley & Sons |
Total Pages | : 312 |
Release | : 2013-05-28 |
Genre | : Science |
ISBN | : 1118691237 |
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 | : Gonzalo Alarcón |
Publisher | : Cambridge University Press |
Total Pages | : 641 |
Release | : 2012-04-26 |
Genre | : Medical |
ISBN | : 0521691583 |
Covers all aspects of epilepsy, from basic mechanisms to diagnosis and management, as well as legal and social considerations.
Author | : Lotfi Chaari |
Publisher | : Springer |
Total Pages | : 0 |
Release | : 2019-07-11 |
Genre | : Medical |
ISBN | : 9783030117993 |
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 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.