Seizure prediction system that combines brain electrical data and cardiorespiratory data

A seizure prediction system that combines brain electrical activity data and cardiorespiratory data, comprising:

• one or more processors coupled to
• an electroencephalogram monitor coupled to a patient and configured to measure electroencephalogram waveforms over time;
• an electrocardiogram monitor coupled to said patient and configured to measure electrocardiogram waveforms over time;
• one or more vital sign sensors coupled to said patient and configured to measure one or more vital signs over time;
• a machine learning system configured to execute on at least one of said one or more processors and trained to calculate a probability that said patient will experience a seizure within a prediction time period;
• a feature extraction system configured to execute on at least one of said one or more processors and configured to
• calculate one or more features, wherein said one or more features comprise:
• one or more neurological features calculated from said electroencephalogram waveforms over time;
• one or more cardiovascular features calculated from said electrocardiogram waveforms over time;
• one or more neurological-cardiovascular relationships calculated from one or more feature pairs, wherein each pair of said one or more feature pairs comprises:
• a neurological feature of said one or more neurological features;
• and
• a cardiovascular feature of said one or more cardiovascular features;
• and,
• one or more vital sign features calculated from said one or more vital signs;
• and,
• input said one or more features into said machine learning system.