Detecting and differentiating nociception events from hemodynamic drug administration events

A system for monitoring arterial pressure of a patient and providing a warning to medical personnel of nociception of the patient, the system comprising:

• a hemodynamic sensor that produces hemodynamic data representative of an arterial pressure waveform of the patient;
• a system memory that stores nociception software code;
• a user interface that includes a sensory alarm that provides a sensory signal to warn the medical personnel of a nociception event of the patient;
• and
• a hardware processor that is configured to execute the nociception software code to:
• perform waveform analysis of the hemodynamic data to determine a plurality of signal measures;
• extract detection input features from the plurality of signal measures that are indicative of the nociception event of the patient;
• extract hemodynamic drug detection input features from the plurality of signal measures that are indicative of a hemodynamic drug administration event of the patient;
• extract hemodynamic drug prediction input features from the plurality of signal measures that are predictive of effects to the patient from a future hemodynamic drug administration event;
• extract stable detection input features from the plurality of signal measures that are indicative of a stable episode of the patient;
• determine a first probability based on the hemodynamic drug prediction input features and the stable detection input features, wherein the first probability represents a probability of the patient experiencing effects from the future hemodynamic drug administration event;
• determine a second probability based on the detection input features and the hemodynamic drug detection input features, wherein the second probability represents a probability of the patient experiencing the current nociception event versus the current hemodynamic drug administration event;
• determine a third probability based on the detection input features and the stable detection input features, wherein the third probability represents a probability of the patient experiencing the current nociception event versus the stable episode;
• compare the third probability with the first probability and the second probability to determine an output probability of the current nociception event of the patient;
• and
• invoke the sensory alarm of the user interface in response to the output probability satisfying a predetermined detection criterion.