Artificial Intelligence to Evaluate Postoperative Pain Based on Facial Expression

Phase

N/A

Condition

Pain

Treatment

N/A

Clinical Study ID

NCT05477303

B-2205-757-304

Ages 19-75
All Genders

Study Summary

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

Eligibility Criteria

Inclusion

Inclusion Criteria:

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

Exclusion

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

Study Design

June 17, 2022

May 09, 2026

Study 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.

Connect with a study center

Seoul National University Bundang Hospital
Seongnam-si, Gyunggi-do 13620
Korea, Republic of
Active - Recruiting

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