Systems and methods for seizure detection based on changes in electroencephalogram (eeg) non-linearities

A method of seizure detection comprising:

• receiving, by a processing circuit, an electroencephalogram (EEG) signal generated based on electrical brain activity of a patient;
• determining, by the processing circuit, a plurality of different types of metrics based on the EEG signal, the plurality of different types of metrics indicating non-linear features of the EEG signal;
• determining, by the processing circuit, whether one or more of the plurality of different types of metrics exhibit changes over time that meet a predefined level of statistical significance;
• generating, by the processing circuit, a user interface, the user interface comprising:
• a real-time trend of the EEG signal;
• and
• the one or more of the plurality of different types of metrics;
• and
• causing, by the processing circuit, a user interface device to display the user interface.

A seizure detection system comprising one or more circuits, the one or more circuits configured to:

• receive an electroencephalogram (EEG) signal generated based on electrical brain activity of a patient;
• determine a plurality of metrics based on the EEG signal, the plurality of metrics indicating non-linear features of the EEG signal by determining a dimensionality of the EEG signal by performing a phase space analysis by increasing a value of the dimensionality until a number of false neighbors reaches zero, wherein a starting value of the dimensionality is based on an age of the patient;
• determine that the EEG signal indicates a candidate seizure by determining, based at least in part on the plurality of metrics, a change in the non-linear features of the EEG signal over time, wherein the change in the non-linear features indicates a physiological force that gives rise to the candidate seizure;
• and
• generate a seizure alert indicating that the EEG signal indicates the candidate seizure.