NCT04914052

Assessment of Postoperative Pain Through Facial Expressions Using Facial Recognition Software

Status unknown Last updated 3 May 2022

What this trial tests

trial testing Filming facial expressions in Pain, Postoperative in 200 participants. Status unknown.

Timeline

25 July 2021

Primary endpoint
1 December 2022

1 July 2023

Quick facts

Lead sponsor	Rabin Medical Center
Status	Status unknown
Study type	OBSERVATIONAL
Enrollment	200
Start date	25 July 2021
Primary completion	1 December 2022
Estimated completion	1 July 2023
Sites	1 location across Israel

Drugs / interventions tested

• Filming facial expressions

Conditions studied

• Pain, Postoperative — all drugs for Pain, Postoperative →

Sponsor

Rabin Medical Center

Who can join

18 and older, any sex, with Pain, Postoperative. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

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.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.