Artificial Intelligence to Evaluate Postoperative Pain Based on Facial Expression

Seoul National University

Status: Enrolling

Conditions: Artificial Intelligence; Pain, Postoperative; Analgesia; Facial Expression

Treatments: Other: taking a picture of a painful facial expression

Study type: Observational

Funder types: Other

Identifiers

NCT05477303

B-2205-757-304

Details and patient eligibility

About

Patients' subjective complaints about pain intensity are difficult to objectively evaluate, and may lead to inadequate pain management, especially in patients with communication difficulties.

Full description

Analgesia nociception index (ANI 0-100) and patient-reported numeric rating scale (NRS 0-10) were trained on a convolutional neural network (CNN) model by linking the patients' facial expression with the score. By applying the predicted pain score by the AI model to evaluate pain, it is intended to measure the intensity of pain in an automatic, fast, and objective way for appropriate pain management.

Enrollment: 120 estimated patients

Sex: All

Ages: 19 to 75 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients aged 19-75 years who were scheduled for elective laparoscopic abdominal surgery under general anesthesia
• American Society of Anesthesiology (ASA) class I-II

Exclusion criteria

• Patients who have difficulty in communicating and reporting pain
• Underlying diseases: liver, kidney, brain
• Patients with BMI greater than 30 and less than 18.5
• Alcohol or drug dependent patients
• Patients with severe or acute respiratory failure
• Opioid, NSAID allergy
• Patients who are scheduled to be admitted to the intensive care unit after surgery
• Patients who undergo cooperative surgery