Our method differs from other methods in that it provides a biologically interpretable perspective to study the brain in healthy and diseased conditions.
In this paper, we have shown that entropy, as an important characterization of the dynamic system, of the EEG signals can be used to discriminate between the ...
Abstract—An epileptic seizure is the irregularity of brain activity that interferes with normal functions. Electroencephalog- raphy (EEG) is widely used for ...
A major theme of this conference is the modeling of electrocortical activity by powerful new tools applicable to nonlinear dynamic systems.
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Feb 1, 2023 · Nonlinear dynamic features are then used to describe EEG signals. Finally, a SVM is used to classify features and diagnose epileptic seizures.
We propose a new seizure detection method based on brain system dynamics. We utilize dynamic distances to distinguish the seizure and normal conditions.
May 23, 2024 · This paper proposed a real-time approach based on EEG signal for detecting epilepsy seizures using the STFT and Google-net convolutional neural network (CNN).
In this study, we propose single-channel, and multi-channel EEG based DMD approaches for the analysis of epileptic EEG signals.
Oct 18, 2023 · In this paper, we propose an EEG-based improved automatic seizure detection system using a Deep neural network (DNN) and Binary dragonfly algorithm (BDFA).
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Mar 15, 2024 · In this study, we developed a machine learning model for automated seizure detection using system identification techniques on EEG recordings.