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A novel algorithm for automated seizure onset detection is presented. The method allows for precise identification of electrographic seizure onset times within large databases of electrographic data.The patient-specific algorithm extracts salient spectral and temporal features in five frequency bands within a sliding window of an electrographic recording. Feature windows are classified as containing...
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