Advancing task recognition towards artificial limbs control with ReliefF-based deep neural network extreme learning
In the rapidly advancing field of biomedical engineering, effective real-time control of
artificial limbs is a pressing research concern. Addressing this, the current study introduces a …
artificial limbs is a pressing research concern. Addressing this, the current study introduces a …
Residual and bidirectional LSTM for epileptic seizure detection
Electroencephalogram (EEG) plays a pivotal role in the detection and analysis of epileptic
seizures, which affects over 70 million people in the world. Nonetheless, the visual …
seizures, which affects over 70 million people in the world. Nonetheless, the visual …
Multiband seizure type classification based on 3D convolution with attention mechanisms
H Huang, P Chen, J Wen, X Lu, N Zhang - Computers in Biology and …, 2023 - Elsevier
Electroencephalogram (EEG) signal contains important information about abnormal brain
activity, which has become an important basis for epilepsy diagnosis. Recently, epilepsy …
activity, which has become an important basis for epilepsy diagnosis. Recently, epilepsy …
EEG-based epileptic seizure detection using deep learning techniques: A survey
J Xu, K Yan, Z Deng, Y Yang, JX Liu, J Wang, S Yuan - Neurocomputing, 2024 - Elsevier
Epilepsy is a complex neurological disorder marked by recurrent seizures, often stemming
from abnormal discharge of the brain. Electroencephalogram (EEG) captures temporal and …
from abnormal discharge of the brain. Electroencephalogram (EEG) captures temporal and …
Using Explainable Artificial Intelligence to obtain efficient seizure-detection models based on electroencephalography signals
Epilepsy is a condition that affects 50 million individuals globally, significantly impacting their
quality of life. Epileptic seizures, a transient occurrence, are characterized by a spectrum of …
quality of life. Epileptic seizures, a transient occurrence, are characterized by a spectrum of …
Wavelet-Hilbert transform based bidirectional least squares grey transform and modified binary grey wolf optimization for the identification of epileptic EEGs
C Liu, W Chen, T Zhang - Biocybernetics and Biomedical Engineering, 2023 - Elsevier
Wavelet based seizure detection is an importance topic for epilepsy diagnosis via
electroencephalogram (EEG), but its performance is closely related to the choice of wavelet …
electroencephalogram (EEG), but its performance is closely related to the choice of wavelet …
Spatiotemporal analysis of interictal EEG for automated seizure detection and classification
Objective Seizure type classification is important as therapy differs for different epilepsy
subtypes. Currently, skilled neurologists classify seizures based on visual analysis …
subtypes. Currently, skilled neurologists classify seizures based on visual analysis …
Automated multi-class seizure-type classification system using EEG signals and machine learning algorithms
Epilepsy is a chronic brain disorder characterized by recurrent unprovoked seizures. The
treatment for epilepsy is influenced by the types of seizures. Therefore, develo** a …
treatment for epilepsy is influenced by the types of seizures. Therefore, develo** a …
[HTML][HTML] Detection of Anxiety-Based Epileptic Seizures in EEG Signals Using Fuzzy Features and Parrot Optimization-Tuned LSTM
KK Palanisamy, A Rengaraj - Brain Sciences, 2024 - mdpi.com
In humans, epilepsy is diagnosed through electroencephalography (EEG) signals. Epileptic
seizures (ESs) arise due to anxiety. The detection of anxiety-based seizures is challenging …
seizures (ESs) arise due to anxiety. The detection of anxiety-based seizures is challenging …
Detection of epileptic seizure events using pre‐trained convolutional neural network, VGGNet and ResNet
Epilepsy is a life threatening neurological disorder. The person with epilepsy suffers from
recurrent seizures. Sudden emission of electrical signal in the nerves of the human brain is …
recurrent seizures. Sudden emission of electrical signal in the nerves of the human brain is …