De-identified UNMH EEG Corpus Database Creation With Fully De-identified Clinical Information

This proposal outlines the steps required for the creation of a pilot database of EEG recordings and de-identified medical records from patients internally referred within the UNMH Comprehensive Epilepsy Center. The UNMH EEG Corpus would be the first database of its kind. Other public databases contain either patient EEG signals or medical records, but without both kinds of information, it is impossible to relate pre-treatment neurobiomarkers with post-treatment prognosis. The database will also contain information that can improve seizure localization based off of scalp and intracranial EEG, and the requisite data for the creation of algorithms that forecast seizure activity; a development that could ultimately lead to novel responsive neural stimulation procedures that suppress seizures before they begin.

Inclusion Criteria: * We will screen with UNMH EEG database, Nihon Kohden Neuroworkbench first. After meeting all the inclusion and exclusion criteria, we will access the Cerner Powerchart (UNMH EMR) for the rest of the clinical information. * 18 years old or older. If the patient's age is over 89, we will aggregated them to age 90 or older so that the patient cannot be identified. Also, all the EEG data will be de-identified and only show the year of the study performed instead of the exact study date to reduce the risk of identification. Of note, we perform over few thousands of EEG studies per year and it will be almost impossible to identify the patient based on the study year. Exclusion Criteria: * Children under age of 18 years old will be excluded. * Mismatched patients between EEG database and EMR