Acute Pain Assessment Using Facial Expression Analysis

NCT ID: NCT03957967

Last Updated: 2020-03-16

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Total Enrollment

1000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2019-05-31

Study Completion Date

2019-11-30

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

Managing pain, which affects 20-50% of the population, is a major issue in daily clinical practice. Evaluation of pain intensity is essential to adapt treatment but as it mainly relies on self-report, this assessment is difficult or impossible in non-communicating patients. In these cases, pain can only be evaluated by medical staff by the observation of pain-related characteristics like facial expression of pain (FEP). However, recognition of FEP is subjective, time-consuming and subject to multiple biases frequently leading to underestimation of pain and consequently under-treatment. Some of these biases could be solved by the use of facial recognition technology, allowing objective, automated and time-saving pain assessment. DEF-I aims to address technical issues and achieve the development of facial expression recognition digital tool able to evaluate severe acute pain in clinical practice, with high validity and utility by improving the quality of the images to be analyzed, by studying larger samples of patients, data and images, in order to correlate more efficiently the pain intensity felt by a patient with the expression of his face. The main objective of this study is to verify whether it is possible to quantitatively correlate the intensity of acute postoperative pain felt by a patient with his facial expression. The secondary objective is to define a reliable computer algorithm that qualitatively correlates the type of acute postoperative pain experienced by a patient with his facial expression.

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Acute Pre and Post Operative Pain

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

acute pain

Patient with acute pain

video taken

Intervention Type OTHER

Patients enrolled will be operated in our institution. Facial expression will be collected before and after surgery, and pain intensity will be collected at the same time. Facial expression will be analyzed using Facial Action Coding System (FACS) .This step will seek to confirm that the subset of Action Units (AUs) defined in previous studies is correlated with the presence and intensity of an acute pain or to identify a different original subset of facial AUs better correlated to pain intensity. . The developed algorithm (or model) here should be able to correlate facial AUs to pain intensity reported by the patients on the numerical rating scale. The developed model at this stage will be then validated on an additional sample of patients.

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

video taken

Patients enrolled will be operated in our institution. Facial expression will be collected before and after surgery, and pain intensity will be collected at the same time. Facial expression will be analyzed using Facial Action Coding System (FACS) .This step will seek to confirm that the subset of Action Units (AUs) defined in previous studies is correlated with the presence and intensity of an acute pain or to identify a different original subset of facial AUs better correlated to pain intensity. . The developed algorithm (or model) here should be able to correlate facial AUs to pain intensity reported by the patients on the numerical rating scale. The developed model at this stage will be then validated on an additional sample of patients.

Intervention Type OTHER

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

* Any adult patient undergoing surgery in our institution during the study duration,
* able to express pain intensity on NRS

Exclusion Criteria

* patient to be operated on in the area of the face or eye
* Patient with altered facial morphology related to a dressing, suture, wound, trauma or oedema on the face
* patient not compliant or unable to clearly express pain
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

Centre Hospitalier Universitaire de Nice

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Responsibility Role SPONSOR

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

Hôpital Pasteur

Nice, , France

Site Status

Countries

Review the countries where the study has at least one active or historical site.

France

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

18-PP-13

Identifier Type: -

Identifier Source: org_study_id

More Related Trials

Additional clinical trials that may be relevant based on similarity analysis.