Intuitively, certain channel signals exhibit weaker correlations with other channels compared to the normal state. Based on this insight, we propose an EEG-based epilepsy detection method with graph ...

The task of EEG data classification involves learning a mapping function f: X → Y, which accurately assigns the appropriate class label yi to each EEG sample Xi based on its brain activity patterns.

The “NEMO” project is exploring anonymisation techniques, using the example of electroencephalograms (EEG) Patient data enjoy extensive protection in Europe. However, this often means that ...

EEG data analysis plays a critical role in neuroscience, diagnostics, and cognitive studies. LightningChart offers robust tools for visualizing large, multi-channel datasets in real-time.

Absence epilepsy is one of the most common types of epilepsy. The diagnosis of absence epilepsy is among the greatest challenges faced by clinical neurologists due to a lack of easily observable ...

The integration of multisensory, particularly the fusion of visual and tactile inputs, plays a crucial role in human perception and environment interaction. Despite its importance, the neural ...

For distance-based EEG graph, we provide the pre-computed adjacency matrix in ./data/electrode_graph. For correlation-based EEG graphs, adjacency matrices can be obtained from the respective ...

This example shows how to use a SAS/GRAPH Web driver to generate a drill-down graph (see About Drill-down Graphs). The example uses the HTML driver, but the principles would be the same for using the ...