Electroencephalogram (EEG) is a standard tool that has been widely used to detect seizures. A number of automated seizure detection systems based on EEG signal classification have been employed in present days, which includes a mixture of approaches but most of them rely on time signal features,...
这些代码能够帮助研究人员和医学专业人士分析EEG信号,并自动检测出可能的癫痫发作事件,有助于及早诊断和治疗癫痫病人。This repository includes useful MATLAB codes for the detection of epileptic seizure in EEG signals using wavelet analysis and machine learning techniques (MLP, SVM, KNN, and Bayesian) ...
The EEG and ECG epochs are then fed into their respective processing unit. The ECG processing unit exploits incoming ECG to make a decision of whether the input ECG signal is of seizure or nonseizure nature. In this unit, Detection based on ECG and HRV In this section, the components ...
Investigation on seizure detection based on deep learning models has achieved great success. However, there still remain challenging issues, such as the high computational complexity of the models and overfitting caused by the scarce availability of ictal electroencephalogram (EEG) signals for training. ...
Epileptic seizure detection is traditionally performed by expert clinicians based on visual observation of EEG signals. This process is time-consuming, burdensome, reliant on expensive human resources, and subject to error and bias. In epilepsy research, on the other hand, manual detection is unsuita...
The method was applied to real clinical EEG data of epileptic patients and evaluated according to sensitivity, specificity, selectivity and average detection rate. The promising results illuminate that hybrid processing approaches in temporal, frequency and spatial domains can be a real solution to ...
Paper tables with annotated results for Unsupervised Multivariate Time-Series Transformers for Seizure Identification on EEG
构建适用于EEG数据的Dynamic GNN模型: 在构建Dynamic GNN模型时,需要根据EEG数据的特点进行定制化设计。例如,可以将EEG电极位置作为图的节点,将电极之间的空间关系作为图的边。 模型可以包括多个图卷积层来提取空间特征,以及LSTM层来捕捉时间依赖性。此外,还可以引入注意力机制来增强模型对重要特征的关注。 训练并验证...
Electroencephalogram (EEG) is one of the main diagnostic tests for epilepsy. The detection of epileptic activity is usually performed by a human expert and is based on finding specific patterns in the multi-channel electroencephalogram. This is a difficu
In XAI4EEG, we combine deep learning models and domain knowledge on seizure detection, namely (a) frequency bands, (b) location of EEG leads and (c) temporal characteristics. XAI4EEG encompasses EEG data preparation, two deep learning models and our proposed explanation module visualizing feature...