Artificial IntelligenceNCT05477303
Artificial Intelligence to Evaluate Postoperative Pain Based on Facial Expression
An observational study of Artificial Intelligence and Facial Expression, run by Seoul National University Bundang Hospital at 1 site in South Korea.
Trial 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. Read more about this study
- Who is it for?
- Ages 19 to 75 years
- Conditions the study is for
- Artificial Intelligence, Facial Expression, Analgesia
- What is being tested?
- taking a picture of a painful facial expression
- How many people
- 120 participants
- Where
- 1 siteSouth Korea
- Study dates
- 17 Jun 2022to 9 May 2026
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 19 to 75 years
- All sexes
- Adult, Older adult
Study population: Patients who were scheduled for elective laparoscopic abdominal surgery under general anesthesia
Who may be able to join
- Patients aged 19-75 years who were scheduled for elective laparoscopic abdominal surgery under general anesthesia
- American Society of Anesthesiology (ASA) class I-II
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country.
South Korea1 site, 1 recruiting
- Recruiting
Seoul National University Bundang Hospital
Seongnam-si, Gyunggi-do, 13620
InSun Park, MD, 82317877507, pis121@hanmail.net
About this study
Official title: Artificial Intelligence to Evaluate Postoperative Pain Based on Facial Expression Recognition and Analgesia Nociception Index
Patients' subjective complaints about pain intensity are difficult to objectively evaluate, and may lead to inadequate pain management, especially in patients with communication difficulties.
Read the detailed 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.
- Being tested
- taking a picture of a painful facial expression
- Medical subject headings
- Facial Expression, Agnosia, Pain, Postoperative
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
taking a picture of a painful facial expressionOther
Immediately after surgery, the patient's facial expression and the NRS score and ANI score reported by the patient are checked together.
What is being measured
The primary outcome is the main question the study is designed to answer.
Facial expression
Painful facial expression
Measured: immediately preoperative, postoperative time
analgesia nociception index
ANI score
Measured: immediately preoperative, postoperative time
numeric rating scale
pain score
Measured: immediately preoperative, postoperative time
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Jul 2022
- Study start17 Jun 2022
- Primary completion20 Apr 2023 (estimated)
- Study completion9 May 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Artificial IntelligenceStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 120 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Seoul National University Bundang Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Park InSun, Seoul National University Bundang Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05477303
- Sponsor's protocol ID
- B-2205-757-304
- Status last verified
- Jul 2022
- First submitted
- 26 Jul 2022
- Last updated
- 28 Jul 2022
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Park I, Park JH, Yoon J, Na HS, Oh AY, Ryu J, Koo BW. Machine learning model of facial expression outperforms models using analgesia nociception index and vital signs to predict postoperative pain intensity: a pilot study. Korean J Anesthesiol. 2024 Apr;77(2):195-204. doi: 10.4097/kja.23583. Epub 2024 Jan 5.
PubMed 38176698Park I, Park JH, Yoon J, Song IA, Na HS, Ryu JH, Oh AY. Artificial intelligence model predicting postoperative pain using facial expressions: a pilot study. J Clin Monit Comput. 2024 Apr;38(2):261-270. doi: 10.1007/s10877-023-01100-7. Epub 2023 Dec 27.
PubMed 38150126
Study at a glance
From the registry record, last updated by the sponsor on 28 Jul 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence to Evaluate Postoperative Pain Based on Facial Expression Recognition and Analgesia Nociception Index
- ClinicalTrials.gov ID
- NCT05477303
- Acronym / sponsor ID
- B-2205-757-304
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 120 participants (estimated)
- Lead sponsor
- Seoul National University Bundang HospitalUniversity, hospital or other
- Study start
- 17 Jun 2022 (actual)
- Primary completion
- 20 Apr 2023 (estimated)
- Study completion
- 9 May 2026 (estimated)
- First posted
- 28 Jul 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Patients' subjective complaints about pain intensity are difficult to objectively evaluate, and may lead to inadequate pain management, especially in patients with communication difficulties.
Detailed 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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 19 to 75 years
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Patients who were scheduled for elective laparoscopic abdominal surgery under general anesthesia
Key inclusion criteria (2 listed)
- Patients aged 19-75 years who were scheduled for elective laparoscopic abdominal surgery under general anesthesia
- American Society of Anesthesiology (ASA) class I-II
Key exclusion criteria (8 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| taking a picture of a painful facial expressionImmediately after surgery, the patient's facial expression and the NRS score and ANI score reported by the patient are checked together. | Other | – |
Primary outcome
Facial expression
Time frame: immediately preoperative, postoperative time
Painful facial expression
analgesia nociception index
Time frame: immediately preoperative, postoperative time
ANI score
numeric rating scale
Time frame: immediately preoperative, postoperative time
pain score
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 28 Jul 2022.
- Derived from this study: PubMed 38176698Park I, Park JH, Yoon J, Na HS, Oh AY, Ryu J, Koo BW. Machine learning model of facial expression outperforms models using analgesia nociception index and vital signs to predict postoperative pain intensity: a pilot study. Korean J Anesthesiol. 2024 Apr;77(2):195-204. doi: 10.4097/kja.23583. Epub 2024 Jan 5.
- Derived from this study: PubMed 38150126Park I, Park JH, Yoon J, Song IA, Na HS, Ryu JH, Oh AY. Artificial intelligence model predicting postoperative pain using facial expressions: a pilot study. J Clin Monit Comput. 2024 Apr;38(2):261-270. doi: 10.1007/s10877-023-01100-7. Epub 2023 Dec 27.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Artificial Intelligence and Facial Expression, run by Seoul National University Bundang Hospital at 1 site in South Korea.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 28 Jul 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in South Korea. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact InSun Park, MD (82317877499, pis121@hanmail.net), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Facial expression (time frame: immediately preoperative, postoperative time). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05477303, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 28 Jul 2022.