Assessment of Postoperative Pain Through Facial Expressions Using Facial Recognition Software

NCT04914052 | Unknown

• 1 other identifier: 0778-20
• Study Type: observational
• Target: 200
• Locations: 1 country
• Sites: 1

Brief Summary

Proper management of postoperative pain is an ongoing medical challenge. Inadequate treatment of pain is associated with significantly worse patient outcomes. However, as pain is a subjective experience accurate assessment is difficult. Commonly used methods for pain assessment include the use of self-reports from patients, or observers assessments. However, both techniques are subjective to bias. Therefore, automatic assessment of pain based on objective data would enable individualized patient care, optimize provided anesthesia treatment and analgesic regimes. While research has shown that facial expressions are valid indicators of pain levels, to date research has yet to yield a reliable clinical tool which can be easily implemented in clinical practice. In this pilot study we intend to assess the feasibility, of facial expression analysis by using machine learning models of artificial intelligence (AI) to accurately predict pain levels of patients experienced in the immediate post operative period. This pilot trial will take place in two stages: First stage will include development of an AI algorithm that correlates facial recognition with pain levels. Second stage will include validation of the algorithm by comparison of to standard pain assessment modalities. In the first stage each assessment of facial expressions will be filmed in a 30 second segment and will be followed by an immediate pain assessment using two modalities, first will be pain score assessed by an anesthesiologist attending the patient at that moment, second will be VAS assessment by the participant patient. Three objective parameters: heart rate, blood pressure and respiratory rate will be recorded simultaneously from the automated record keeping system used in every patient in the recovery room (post anesthesia care unit-PACU). These assessments will take place at different time intervals according to the investigator's decision, throughout the participant's staying in the post anesthesia care unit. After completion of the first stage, the second stage of the study will be done in the same manner as described above regarding patients enrollment. Pain assessment will be done by VAS and physician assessment as described above but this time will be correlated with pain assessment by the algorithm developed in the first stage of the study.

Conditions

Pain, Postoperative

Outcome Measures

Primary Outcomes (1)

• visual analog scale of pain (VAS)

  vas scores of pain from 0-10 a lower number reflecting a lower measure of pain the study will try to correlate VAS scores with automatic facial expression , accurately reflecting the pain intensity measurements of patients in the immediate post-operative period during duration in the PACU ( post anesthesia care unit).

  stay during pacu up to 6 hours

Secondary Outcomes (1)

• automatic analysis of facial expressions and observer pain assessment scores.

  stay during pacu up to 6 hours

Study Arms (1)

Study group

Patients will be requested to sign an informed consent in which they will agree to have their face filmed in the post-anesthesia care unit. The facial expressions will be filmed in 30 second segments. A pain assessment will be measured immediately following filming of each segment using two modalities: * Pain score assessed by an attending anesthesiologist assigned to the study team. * VAS assessment by the patient. Following data collection, the data will be forwarded in a coded manner, according to Clalit's data security regulations, to Third Eye systems a facial recognition software company. Third Eye systems will analyze and process the data using AI and machine learning models and develop an algorithm that can predict pain level by watching facial expressions.

Other: Filming facial expressions

Interventions

Filming facial expressions OTHER

Study participants' facial expressions will be videoed by a camera placed in front of the patient's bed during their stay in the post anesthesia care unit.

Study group

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

patients above 18 presenting for an elective surgery at Beilinson Hospital

You may qualify if:

• All patients above 18 presenting for an elective surgery at Beilinson Hospital following obtaining written informed consents form with the ability to comply with the study requirements will be included in our study.

You may not qualify if:

• Patients under the age of 18
• Patients unable to sign an informed consent
• Patients with a history of psychiatric disease.

Sponsors & Collaborators

• Rabin Medical Center: lead
• Third eye systems: collaborator

Study Sites (1)

Rabin Medical Center/Beilinson Campus

Petah Tikva, 49100, Israel

RECRUITING

MeSH Terms

Conditions

Pain, Postoperative

Condition Hierarchy (Ancestors)

Postoperative Complications; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Pain; Neurologic Manifestations; Signs and Symptoms

Central Study Contacts

Leonid Eidelman

CONTACT

039376850; leidelman@clalit.org.il

Atara Davis

CONTACT

972533321329; ataratdavis@gmail.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 30, 2021
• First Posted: June 4, 2021
• Study Start: July 25, 2021
• Primary Completion: December 1, 2022
• Study Completion: July 1, 2023
• Last Updated: May 3, 2022

Record last verified: 2021-05

Locations

IL (1)