Multiscale Distribution Entropy Analysis of Short Epileptic EEG Signals
Published
Research approach
Preserved samples through moving averages and compared multiscale distribution entropy for state separation in short EEG.
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Results
Evaluated scale-wise ROC AUC on Bonn and Bern-Barcelona EEG, focusing on sample loss at larger scales.
| Samples at scale s | For a sequence of length N |
|---|---|
| Coarse-graining | floor(N / s) |
| Moving average | N - s + 1 |
| Evaluation | State separation in public EEG |
InterpretationThe Bonn A segment is a five-second interval centered on the first quartile. ROC AUC measures state separation in public EEG datasets. Bern-Barcelona evaluation distinguishes focal from non-focal EEG.
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