Systems and methods to monitor nociception, pain, and pain relief

A system for monitoring nociception and/or pain in a patient during surgery, the system comprising:

• a control unit;
• a first input device to provide event detection information corresponding to a surgical event to the control unit;
• a second input device to provide physiological data to the control unit;
• a third input device to provide functional near-infrared spectroscopy (fNIRS) data from a medial frontopolar cortex region and a somatosensory region of the patient to the control unit;
• and
• an output device to provide information to a user,
• wherein the control unit is to:
• process the event detection information, the physiological data, and the fNIRS data to obtain processed data,
• input the processed data to a machine learning classifier that classifies the surgical event as a pain event or a no-pain event, and
• control the output device to provide the classification from the classifier to the user.

A method of detecting nociception and pain in a patient, the method comprising:

• obtaining functional near-infrared spectroscopy (fNIRS) data from a medial frontopolar cortex (mFPC) region and a somatosensory (S1) region of the patient;
• recognizing signatures in the fNIRS data associated with a pain event in real time, wherein the signatures include a dissociation between the fNIRS data from the mFPC region and the fNIRS data from the S1 region;
• and
• outputting a pain event classification to a user based on recognizing the signatures.