Automatic seizure detection using orthogonal matching pursuit, discrete wavelet transform, and entropy based features of EEG signals
Background and objective Epilepsy is a prevalent disorder that affects the central nervous
system, causing seizures. In the current study, a novel algorithm is developed using …
system, causing seizures. In the current study, a novel algorithm is developed using …
Application of machine learning in epileptic seizure detection
Epileptic seizure is a neurological condition caused by short and unexpectedly occurring
electrical disruptions in the brain. It is estimated that roughly 60 million individuals worldwide …
electrical disruptions in the brain. It is estimated that roughly 60 million individuals worldwide …
Generalized Stockwell transform and SVD-based epileptic seizure detection in EEG using random forest
T Zhang, W Chen, M Li - Biocybernetics and Biomedical Engineering, 2018 - Elsevier
Purpose Visual inspection of electroencephalogram (EEG) records by neurologist is the
main diagnostic method of epilepsy but it is particularly time-consuming and expensive …
main diagnostic method of epilepsy but it is particularly time-consuming and expensive …
Automatic epileptic seizure detection in EEG signals using multi-domain feature extraction and nonlinear analysis
Epileptic seizure detection is commonly implemented by expert clinicians with visual
observation of electroencephalography (EEG) signals, which tends to be time consuming …
observation of electroencephalography (EEG) signals, which tends to be time consuming …
An EEG based real-time epilepsy seizure detection approach using discrete wavelet transform and machine learning methods
M Shen, P Wen, B Song, Y Li - Biomedical Signal Processing and Control, 2022 - Elsevier
Epilepsy is one of the most common complex brain disorders which is a chronic non-
communicable disease caused by paroxysmal abnormal super-synchronous electrical …
communicable disease caused by paroxysmal abnormal super-synchronous electrical …
An automated detection of epileptic seizures EEG using CNN classifier based on feature fusion with high accuracy
W Chen, Y Wang, Y Ren, H Jiang, G Du… - BMC Medical informatics …, 2023 - Springer
Background Epilepsy is a neurological disorder that is usually detected by
electroencephalogram (EEG) signals. Since manual examination of epilepsy seizures is a …
electroencephalogram (EEG) signals. Since manual examination of epilepsy seizures is a …
Automated detection of epileptic seizures using successive decomposition index and support vector machine classifier in long-term EEG
Epilepsy is a commonly observed long-term neurological disorder that impairs nerve cell
activity in the brain and has a severe impact on people's daily lives. Accurate seizure …
activity in the brain and has a severe impact on people's daily lives. Accurate seizure …
A novel approach based on wavelet analysis and arithmetic coding for automated detection and diagnosis of epileptic seizure in EEG signals using machine learning …
Epilepsy, a common neurological disorder, is generally detected by electroencephalogram
(EEG) signals. Visual inspection and interpretation of EEGs is a slow, time consuming …
(EEG) signals. Visual inspection and interpretation of EEGs is a slow, time consuming …
Enhanced detection of epileptic seizure using EEG signals in combination with machine learning classifiers
W Mardini, MMB Yassein, R Al-Rawashdeh… - IEEE …, 2020 - ieeexplore.ieee.org
Electroencephalogram (EEG) is one of the most powerful tools that offer valuable
information related to different abnormalities in the human brain. One of these abnormalities …
information related to different abnormalities in the human brain. One of these abnormalities …
Automatic epilepsy detection using wavelet-based nonlinear analysis and optimized SVM
M Li, W Chen, T Zhang - Biocybernetics and biomedical engineering, 2016 - Elsevier
Aiming at the problems of low accuracy, poor universality and functional singleness for
seizure detection, an effective approach using wavelet-based non-linear analysis and …
seizure detection, an effective approach using wavelet-based non-linear analysis and …
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