This data augmentation improves the dimensionality of the EEG dataset, thus improving feature extraction and classification accuracy for various sub-bands of EEG signals, including delta, theta, alpha, beta, and raw signals.
An automated ES detection framework based on the De-mixing Multivariate Variational Mode Decomposition (D-MVMD) integrated with the Bayesian Optimized Support Vector Machine (BO-SVM) proves itself to be an effective and robust model for detecting seizures using the multichannel EEG analysis.
T. V. Manju, M. Hota· IEEE journal of biomedical a...· 0 citations
A Deep Hybrid Neural Network framework that combines Convolutional Neural Networks (CNN) with the Aquila Optimizer (AO) for the automatic detection of epileptic seizures utilizing EEG data in MATLAB is introduced.
Swati Chowdhuri, Tiyasha Mondal· International Journal of Eng...· 0 citations
EEG (Electroencephalography) is a signal that records the electrical activity of the brain. This experimental signal is used to evaluate the electrical activity of the brain, which is used to detect possible problems in communication between brain cells. In addition, EEG can be used for Human-Computer Interaction (HCI)...
The proposed improved FSWT method can be used for EOG artifact suppression in single-channel EEG signals without relying on multichannel spatial redundancy and could reduce the high-amplitude fluctuations caused by eye blinks while preserving the main EEG rhythm structures under real-world acquisition conditions.
Hao-Yu Fu, Mingfu Zhao, Lu-Rui Wang et al.· Sheng wu yi xue gong cheng x...· 0 citations
Epilepsy affects approximately 50 million people worldwide, and timely, accurate seizure detection is essential for clinical management. Electroencephalogram (EEG) signals carry rich temporal and spectral information about brain dynamics, yet manual interpretation is time-consuming and expert-dependent. This paper pres...
Faiza Dad, Fred Lacy, Yasser Ismail· Algorithms· 0 citations
FGPT adaptively represents global EEG rhythms by introducing learnable sparse frequency prompt tokens and synergistically embeds these tokens with the original EEG sequence into the Transformer's self-attention computation, which enables joint modeling of spatio-temporal and frequency-domain features without compromisi...
Hanzhong Tan, Shuangbing Wen, Tao Hu et al.· IEEE journal of biomedical a...· 0 citations
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