EEG classification has received much attention in computer-aided diagnosis for seizure. However, the present feature extraction strategies lead to uninterpretable features to which human vision is not sensitive, and due to the lack of explicit knowledge consistent with human intuition in such features,...
This work focuses on automated epileptic seizure diagnosis (ESD) and prediction (ESP) to clarify the expanding role of machine learning (ML) in epileptic analysis. It outlines the current approaches and challenges in the diagnosis and prognosis of epilepsy and examines the convergence of magnetic ...
whileignoringthegraphicalstructuralinformationpresentinEEGsignals.Whenaseizureoccurs,theelectrodesplacedonthescalpneartheepilepticfocuswillhaveobviousandconsistentvoltagechanges,sohowtoconvolutetheadjacentelectrodesandextracthigh-levelfeaturesisthekeywork.Inthedissertation,anovelapproachtoepilepticdetectionbasedontheHierarchy...
Keywords: Electroencephalogram; Epileptic Seizure; Automatic Diagnostic Systems; Feature Analysis; Recognitiondoi:10.4236/jbise.2011.412097Yuedong SongJournal of Biomedical Science & EngineeringY. Song, "A review of developments of EEG-based automatic medical support systems for epilepsy diagnosis and seizure...
(EMD), and the Wigner-Ville distribution (WVD). The articles in Table2investigated various methods for EEG signal analysis, including the use of rational discrete STFT and deep learning for epileptic seizure classification, a hybrid approach for alcohol and control EEG signal classification, ...
EEG signals effectively and to detect epileptic seizures.The signals of the EEG channels within a second-time window are optically encoded as inputs to the constructed diffractive neural networks for classification, which monitors the brain state to identify symptoms of an epileptic seizure. We...
Feature extraction and selection from electroencephalogram signals for epileptic seizure diagnosis Dionathan Luan de Vargas Jefferson Tales Oliva João Luís Garcia Rosa Neural Computing and Applications(2023) Effects of short- and long-term neurostimulation (tDCS) on Alzheimer’s disease patients: two ra...
is the most important investigation in the diagnosis and management of epilepsies, providing it is properly performed and carefully interpreted in the context of a well described clinical setting.1 2The current practice in paediatrics of not requesting an EEG after the "first afebrile seizure"2 may...
and then record the electrical signals produced by the brain. Typically, diagnosis using EEG signals is carried out using the knowledge and experience of experts, based on visual inspection of the seizure signals recorded during EEG sessions. However this process is subject to errors, expensive and...
To evaluate an automated seizure detection (ASD) algorithm in EEGs with periodic and other challenging patterns. Selected EEGs recorded in patients over 1y... O Gibson,CJ James - IFMBE 被引量: 12发表: 2002年 RETRACTED: A novel real-time patient-specific seizure diagnosis algorithm based on ...