Pain, PostoperativeNCT04914052
Assessment of Postoperative Pain Through Facial Expressions Using Facial Recognition Software
An observational study of Pain, Postoperative, run by Rabin Medical Center at 1 site in Israel.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Pain, Postoperative
- What is being tested?
- Filming facial expressions
- How many people
- 200 participants
- Where
- 1 siteIsrael
- Study dates
- 25 Jul 2021to 1 Jul 2023
- 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 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: patients above 18 presenting for an elective surgery at Beilinson Hospital
Who may be able to join
- 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.
Who cannot join
- Patients under the age of 18
- Patients unable to sign an informed consent
- Patients with a history of psychiatric disease.
Trial locations and contacts
1 site in 1 country.
Israel1 site, 1 recruiting
- Recruiting
Rabin Medical Center/Beilinson Campus
Petah Tikva, 49100
Binyamin Zerbi, M.D.
About this study
Official title: Assessment of Postoperative Pain Through Facial Expressions Using Facial Recognition Software: a Prospective Observational Feasibility Study
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.
Read more
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.
Read the detailed description
After consenting to participation patients will undergo an explanation on pain assessment using VAS and then will proceed with surgery, inclusion in the study will not affect anesthesia or surgery management in any way.
Study participation will take place in the PACU. Upon admission to the PACU unit, all study participants' facial expressions will be videoed by a camera placed in front of the patient's bed.
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.
- 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 PACU The quantity of segments filmed for each of the participants will be decided by the investigator taking into account participant's cooperation level and VAS levels.
In order to engineer an accurate predictive model the dataset will also include participants reporting a VAS of 0- experiencing no pain.
Data Management:
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.
For first stage 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.
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.
This feasibility study is pilot study to examine whether there is a positive correlation, on a relatively small sample size analysis, using simple resources and limited data to perform this study.
In the event that a positive hypothesis can be confirmed, a second stage observational study with a large sample size and an increased data source will be investigated.
- Conditions
- Pain, Postoperative
- Being tested
- Filming facial expressions
- Medical subject headings
- Pain, Postoperative
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Filming facial expressionsOther
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 | Role | What they receive |
|---|---|---|
| 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. Receives: Other: Filming facial expressions |
What is being measured
The primary outcome is the main question the study is designed to answer.
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).
Measured: stay during pacu up to 6 hours
Secondary outcomes (1)
automatic analysis of facial expressions and observer pain assessment scores.
Our secondary endpoint is to examine whether automatic analysis of facial expressions correspond with observer pain assessment scores.
Measured: stay during pacu up to 6 hours
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 Jun 2021
- Study start25 Jul 2021
- Primary completion1 Dec 2022 (estimated)
- Study completion1 Jul 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pain, PostoperativeStudies 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
- 200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Rabin Medical Center
- Sponsor type
- University, hospital or other
- Collaborators
- Third eye systems
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04914052
- Sponsor's protocol ID
- 0778-20
- Status last verified
- May 2021
- First submitted
- 30 May 2021
- Last updated
- 3 May 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 3 May 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Assessment of Postoperative Pain Through Facial Expressions Using Facial Recognition Software: a Prospective Observational Feasibility Study
- ClinicalTrials.gov ID
- NCT04914052
- Acronym / sponsor ID
- 0778-20
- Conditions
- Pain, Postoperative
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- Rabin Medical CenterUniversity, hospital or other
- Collaborators
- Third eye systems
- Study start
- 25 Jul 2021 (actual)
- Primary completion
- 1 Dec 2022 (estimated)
- Study completion
- 1 Jul 2023 (estimated)
- First posted
- 4 Jun 2021 (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.
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.
Detailed description
After consenting to participation patients will undergo an explanation on pain assessment using VAS and then will proceed with surgery, inclusion in the study will not affect anesthesia or surgery management in any way.
Study participation will take place in the PACU. Upon admission to the PACU unit, all study participants' facial expressions will be videoed by a camera placed in front of the patient's bed.
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.
- 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 PACU The quantity of segments filmed for each of the participants will be decided by the investigator taking into account participant's cooperation level and VAS levels.
In order to engineer an accurate predictive model the dataset will also include participants reporting a VAS of 0- experiencing no pain.
Data Management:
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.
For first stage 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.
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.
This feasibility study is pilot study to examine whether there is a positive correlation, on a relatively small sample size analysis, using simple resources and limited data to perform this study.
In the event that a positive hypothesis can be confirmed, a second stage observational study with a large sample size and an increased data source will be investigated.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Study group | – | Other: Filming facial expressionsPatients 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- patients above 18 presenting for an elective surgery at Beilinson Hospital
Key inclusion criteria (1 listed)
- 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.
Key exclusion criteria (3 listed)
- Patients under the age of 18
- Patients unable to sign an informed consent
- Patients with a history of psychiatric disease.
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 |
|---|---|---|
| Filming facial expressionsStudy 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. | Other | Study group |
Primary outcome
visual analog scale of pain (VAS)
Time frame: stay during pacu up to 6 hours
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).
1 secondary outcome
automatic analysis of facial expressions and observer pain assessment scores.
Time frame: stay during pacu up to 6 hours
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 May 2022.
- 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 Pain, Postoperative, run by Rabin Medical Center at 1 site in Israel.
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 1 inclusion and 3 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 3 May 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 Israel. 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 Leonid Eidelman (039376850, leidelman@clalit.org.il), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
visual analog scale of pain (VAS) (time frame: stay during pacu up to 6 hours). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 3 May 2022.