Abstract: Systems and methods of the present disclosure enable improved seizure detection and/or prediction using a seizure monitoring system. The system receives a data stream including wearable sensor data associated with a user, where the data stream includes electrodermal activity data and where the electrodermal activity data includes circadian rhythm-dependent amplitudes. The system receives a time associated with a seizure of the user. The system trains seizure machine learning model to identify a pre-ictal period associated with a time segment based on the circadian rhythm dependent amplitudes and the time associated with the seizure. The system deploys the seizure machine learning model to ingest a new data stream. Based on the new data stream, the seizure machine learning model predicts a seizure likelihood in a prediction period.