System and methods for proposing detection parameters for detecting epileptiform activity

A system for proposing a detection tool for an implanted medical device (IMD) of a patient, wherein the detection tool detects for an event in EEG signals sensed by the IMD, the system comprising:

• a memory;
• and
• a processor coupled to the memory and configured to:
• apply a machine learning based model to a plurality of EEG records of the patient to identify a set of EEG records with electrographic activity indicative of an electrographic seizure, where the EEG records comprise a plurality of channel EEG signals sensed by a corresponding plurality of sensing channels of the IMD;
• apply a machine learning based model to the identified set of EEG records to identify channel EEG signals having an earliest seizure onset;
• and
• for each of the identified channel EEG signals:
• process each of a plurality of regions of interest (ROI) of the identified channel EEG signal to implement a corresponding plurality of candidate detection tools to detect the event;
• apply each candidate detection tool of the plurality of candidate detection tools to a simulation set of electrographic signals to determine a respective set of metrics;
• and
• process the respective sets of metrics to identify a selected detection tool from among the candidate detection tools.