Fibromyalgia (FM)FibromyalgiaNCT06813352
Analysis of Facial Expressions for Pain Recognition in Fibromyalgia: Using Artificial Intelligence and Biomarkers
An observational study of Fibromyalgia (FM) and Pain, run by Faculdade de Ciências Médicas de Minas Gerais at 1 site in Brazil.
Trial summary
Fibromyalgia (FM) is a chronic musculoskeletal pain syndrome with characteristics of generalized body pain, low pain threshold, tenderness and stiffness in muscles, tendons and joints. The assessment of pain in this condition is a challenge due to its subjective nature. Read more about this study
- Who is it for?
- Ages 18 to 65 yearsHealthy volunteers can take part
- Conditions the study is for
- Fibromyalgia (FM), Pain, Catastrophizing Pain
- How many people
- 122 participants
- Where
- 1 siteBrazil
- Study dates
- 17 Nov 2025to 1 Sep 2026
- How long will I take part?
- 1 Day
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 to 65 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: The study will be carried out with adult patients aged between 18 and 65 diagnosed with fibromyalgia at the outpatient clinic of the Faculdade Ciências Médicas de Minas Gerais and Clínica Ampla de Reumatologia in Belo Horizonte. The inclusion criteria were patients with no diagnosed cognitive deficit and who were willing to take part in the study. The exclusion criteria are patients who use medication that can affect anxiety or depression or who are unable to understand the instructions. Thus, once the patients agree to participate, they will be asked to sign the Informed Consent Form (ICF), which will provide detailed information about the nature of the study, the criteria for participation, the possible risks and benefits involved.
Who may be able to join
- The inclusion criteria are patients with no diagnosed cognitive deficit and who are willing to take part in the study.
Who cannot join
- Exclusion criteria are patients who use medication that can affect anxiety or depression or inability to understand the instructions.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Brazil1 site, 1 recruiting
- Recruiting
Outpatient Faculty Medical Sciences
Belo Horizonte, Minas Gerais, 30130110
About this study
Official title: Analysis of Facial Expressions for Pain Recognition: Using Artificial Intelligence and Biomarkers as a Pain Diagnostic Tool in Fibromyalgia, a Pilot Study
Fibromyalgia (FM) is a chronic musculoskeletal pain syndrome with characteristics of generalized body pain, low pain threshold, tenderness and stiffness in muscles, tendons and joints. The assessment of pain in this condition is a challenge due to its subjective nature. A promising approach to assessing pain intensity is facial expression analysis, which can serve as an objective indicator. In addition, research seeks to identify molecular molecular markers to quantify pain. However, the lack of a standardized system has made it difficult to identify reliable markers. In summary, the search for objective methods of assessing pain in fibromyalgia is essential in order to develop more effective more effective treatments. Facial expression analysis and the investigation of molecular markers are promising ways of quantifying pain intensity more accurately and intensity of pain more accurately and reliably in fibromyalgia.
Read the detailed description
Introduction:
Fibromyalgia (FM) is a chronic syndrome characterized by diffuse musculoskeletal pain, fatigue and sleep disturbances, with a major impact on quality of life. Due to the subjectivity of pain assessment, the development of objective methods is essential. This study explores the use of artificial intelligence (AI) in the analysis of facial expressions, combined with the investigation of molecular markers, as an innovative and quantitative approach to pain assessment in patients with FM.
Objective:
To validate the application of an AI tool combined with facial expression analysis and molecular biomarker research to measure pain intensity in FM patients.
Methodology:
An observational cohort study was carried out with 122 participants, divided into two groups: patients with FM (n=61) and without FM (n=61). Data collection included:
- Facial expression recording: A convolutional neural network algorithm was used to analyze facial patterns associated with pain.
- Biological samples: 1mL of saliva will be collected from each participant using the salivette method and processed to extract DNA, RNA and plasma proteins. The proteins will be quantified by ELISA and the genes associated with FM will be analyzed by RT-qPCR.
- Clinical Questionnaires: Psychometric instruments such as the Visual Analogue Scale (VAS) and the Generalized Pain Index (GDI) were used to validate the results.
- Statistical analysis: The data was analyzed using Kappa and Bland-Altman correlations to assess the agreement between the AI methods and the questionnaires, with a significance level of p<0.05.
The AI algorithm will use consistent facial patterns correlating them to the reported pain intensity, in agreement (Kappa=0.82) with the results of the clinical scales.The molecular markers analyzed are expected to show significant differences between the groups, with increased expression of inflammatory proteins in FM patients (p<0.05). The integration of facial and molecular analysis aims to amplify the accuracy of pain intensity classification.
This approach represents a promising advance in the diagnosis and management of the syndrome, contributing to personalized therapies and improving patients' quality of life.
- Conditions
- Fibromyalgia (FM), Pain, Catastrophizing Pain
- Keywords
- Fibromyalgia, Artificial intelligence, Molecular biomarkers, Catastrophism, Facial expression
- Medical subject headings
- Fibromyalgia, Pain, Facial Expression
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Patients diagnosed with fibromyalgia | The aim is to follow fibromyalgia patients over a period of months to analyze pain intensity and identify molecular markers associated with the condition. The study encompasses facial analysis techniques and molecular markers, along with artificial intelligence tools, to quantify pain and understand the underlying mechanisms of fibromyalgia. The methodology is predominantly quantitative, focused on collecting and analyzing objective data on pain and associated markers. | |
| Patients without a diagnosis of fibromyalgia | The aim is to follow patients with pain over a period of months to analyze the intensity and identify molecular markers associated with the condition. The study encompasses facial analysis techniques and molecular markers, along with artificial intelligence tools, to quantify pain and understand the underlying mechanisms of fibromyalgia. The methodology is predominantly quantitative, focused on collecting and analyzing objective data on pain and associated markers. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Use the artificial intelligence tool to analyze the facial expression of patients with fibromyalgia in order to recognize pain.
Use the artificial intelligence tool to analyze the facial expression of patients with fibromyalgia in order to recognize pain. 61 patients with fibromyalgia will be compared with 61 patients without fibromyalgia.
Measured: The estimated time for the anamnesis is one hour, during which time biological samples will be taken and each patient's facial expressions will be recorded on camera.
Secondary outcomes (1)
Biochemical analysis of biomarkers in the detection of pain in fibromyalgia.
122 samples containing 1ml of saliva will be collected in order to check for changes in oxidative stress and nociceptive markers (by spectrophotometry and ELISA).
Measured: Estimated collection and analysis time: 5 hours of durability
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Feb 2025
- Study start17 Nov 2025
- Primary completion1 Feb 2026 (estimated)
- Study completion1 Sep 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Fibromyalgia (FM)Studies 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
- Cross-sectional
- Enrolment
- 122 participants (estimated)
- Target duration
- 1 Day
Sponsor and investigators
- Lead sponsor
- Faculdade de Ciências Médicas de Minas Gerais
- Sponsor type
- University, hospital or other
- Collaborators
- Fundação de Amparo à Pesquisa do estado de Minas Gerais, Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Responsible party
- Principal investigator, Alessandra Hubner de Souza, Faculdade de Ciências Médicas de Minas Gerais
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06813352
- Sponsor's protocol ID
- CMMG
- Acronym
- Fibromyalgia
- Status last verified
- Feb 2025
- First submitted
- 19 Dec 2024
- Last updated
- 19 Nov 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Barua VB, Juel MAI, Blackwood AD, Clerkin T, Ciesielski M, Sorinolu AJ, Holcomb DA, Young I, Kimble G, Sypolt S, Engel LS, Noble RT, Munir M. Tracking the temporal variation of COVID-19 surges through wastewater-based epidemiology during the peak of the pandemic: A six-month long study in Charlotte, North Carolina. Sci Total Environ. 2022 Mar 25;814:152503. doi: 10.1016/j.scitotenv.2021.152503. Epub 2021 Dec 23.
PubMed 34954186Agarwal A, Emary PC, Gallo L, Oparin Y, Shin SH, Fitzcharles MA, Adachi JD, Cooper MD, Craigie S, Rai A, Wang L, Couban RJ, Busse JW. Physicians' knowledge, attitudes, and practices regarding fibromyalgia: A systematic review and meta-analysis of cross-sectional studies. Medicine (Baltimore). 2024 Aug 2;103(31):e39109. doi: 10.1097/MD.0000000000039109.
PubMed 39093781Ahmad M, Ahmed I, Jeon G. A sustainable advanced artificial intelligence-based framework for analysis of COVID-19 spread. Environ Dev Sustain. 2022 Aug 16:1-16. doi: 10.1007/s10668-022-02584-0. Online ahead of print.
PubMed 35993085
Study at a glance
From the registry record, last updated by the sponsor on 19 Nov 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Analysis of Facial Expressions for Pain Recognition: Using Artificial Intelligence and Biomarkers as a Pain Diagnostic Tool in Fibromyalgia, a Pilot Study
- ClinicalTrials.gov ID
- NCT06813352
- Acronym / sponsor ID
- Fibromyalgia / CMMG
- Conditions
- Fibromyalgia (FM), Pain, Catastrophizing Pain
- Keywords
- Fibromyalgia, Artificial intelligence, Molecular biomarkers, Catastrophism, Facial expression
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 122 participants (estimated)
- Lead sponsor
- Faculdade de Ciências Médicas de Minas GeraisUniversity, hospital or other
- Collaborators
- Fundação de Amparo à Pesquisa do estado de Minas Gerais, Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Study start
- 17 Nov 2025 (actual)
- Primary completion
- 1 Feb 2026 (estimated)
- Study completion
- 1 Sep 2026 (estimated)
- First posted
- 6 Feb 2025 (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.
Fibromyalgia (FM) is a chronic musculoskeletal pain syndrome with characteristics of generalized body pain, low pain threshold, tenderness and stiffness in muscles, tendons and joints. The assessment of pain in this condition is a challenge due to its subjective nature. A promising approach to assessing pain intensity is facial expression analysis, which can serve as an objective indicator. In addition, research seeks to identify molecular molecular markers to quantify pain. However, the lack of a standardized system has made it difficult to identify reliable markers. In summary, the search for objective methods of assessing pain in fibromyalgia is essential in order to develop more effective more effective treatments. Facial expression analysis and the investigation of molecular markers are promising ways of quantifying pain intensity more accurately and intensity of pain more accurately and reliably in fibromyalgia.
Detailed description
Introduction:
Fibromyalgia (FM) is a chronic syndrome characterized by diffuse musculoskeletal pain, fatigue and sleep disturbances, with a major impact on quality of life. Due to the subjectivity of pain assessment, the development of objective methods is essential. This study explores the use of artificial intelligence (AI) in the analysis of facial expressions, combined with the investigation of molecular markers, as an innovative and quantitative approach to pain assessment in patients with FM.
Objective:
To validate the application of an AI tool combined with facial expression analysis and molecular biomarker research to measure pain intensity in FM patients.
Methodology:
An observational cohort study was carried out with 122 participants, divided into two groups: patients with FM (n=61) and without FM (n=61). Data collection included:
- Facial expression recording: A convolutional neural network algorithm was used to analyze facial patterns associated with pain.
- Biological samples: 1mL of saliva will be collected from each participant using the salivette method and processed to extract DNA, RNA and plasma proteins. The proteins will be quantified by ELISA and the genes associated with FM will be analyzed by RT-qPCR.
- Clinical Questionnaires: Psychometric instruments such as the Visual Analogue Scale (VAS) and the Generalized Pain Index (GDI) were used to validate the results.
- Statistical analysis: The data was analyzed using Kappa and Bland-Altman correlations to assess the agreement between the AI methods and the questionnaires, with a significance level of p<0.05.
The AI algorithm will use consistent facial patterns correlating them to the reported pain intensity, in agreement (Kappa=0.82) with the results of the clinical scales.The molecular markers analyzed are expected to show significant differences between the groups, with increased expression of inflammatory proteins in FM patients (p<0.05). The integration of facial and molecular analysis aims to amplify the accuracy of pain intensity classification.
This approach represents a promising advance in the diagnosis and management of the syndrome, contributing to personalized therapies and improving patients' quality of life.
Study design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Target follow-up
- 1 Day
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Patients diagnosed with fibromyalgia | – | –The aim is to follow fibromyalgia patients over a period of months to analyze pain intensity and identify molecular markers associated with the condition. The study encompasses facial analysis techniques and molecular markers, along with artificial intelligence tools, to quantify pain and understand the underlying mechanisms of fibromyalgia. The methodology is predominantly quantitative, focused on collecting and analyzing objective data on pain and associated markers. |
| Patients without a diagnosis of fibromyalgia | – | –The aim is to follow patients with pain over a period of months to analyze the intensity and identify molecular markers associated with the condition. The study encompasses facial analysis techniques and molecular markers, along with artificial intelligence tools, to quantify pain and understand the underlying mechanisms of fibromyalgia. The methodology is predominantly quantitative, focused on collecting and analyzing objective data on pain and associated markers. |
Who may qualify
- Ages
- 18 to 65 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- The study will be carried out with adult patients aged between 18 and 65 diagnosed with fibromyalgia at the outpatient clinic of the Faculdade Ciências Médicas de Minas Gerais and Clínica Ampla de Reumatologia in Belo Horizonte. The inclusion criteria were patients with no diagnosed cognitive deficit and who were willing to take part in the study. The exclusion criteria are patients who use medication that can affect anxiety or depression or who are unable to understand the instructions. Thus, once the patients agree to participate, they will be asked to sign the Informed Consent Form (ICF), which will provide detailed information about the nature of the study, the criteria for participation, the possible risks and benefits involved.
Key inclusion criteria (1 listed)
- The inclusion criteria are patients with no diagnosed cognitive deficit and who are willing to take part in the study.
Key exclusion criteria (1 listed)
- Exclusion criteria are patients who use medication that can affect anxiety or depression or inability to understand the instructions.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Use the artificial intelligence tool to analyze the facial expression of patients with fibromyalgia in order to recognize pain.
Time frame: The estimated time for the anamnesis is one hour, during which time biological samples will be taken and each patient's facial expressions will be recorded on camera.
Use the artificial intelligence tool to analyze the facial expression of patients with fibromyalgia in order to recognize pain. 61 patients with fibromyalgia will be compared with 61 patients without fibromyalgia.
1 secondary outcome
Biochemical analysis of biomarkers in the detection of pain in fibromyalgia.
Time frame: Estimated collection and analysis time: 5 hours of durability
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Nov 2025.
- Background: PubMed 34954186Barua VB, Juel MAI, Blackwood AD, Clerkin T, Ciesielski M, Sorinolu AJ, Holcomb DA, Young I, Kimble G, Sypolt S, Engel LS, Noble RT, Munir M. Tracking the temporal variation of COVID-19 surges through wastewater-based epidemiology during the peak of the pandemic: A six-month long study in Charlotte, North Carolina. Sci Total Environ. 2022 Mar 25;814:152503. doi: 10.1016/j.scitotenv.2021.152503. Epub 2021 Dec 23.
- Background: PubMed 39093781Agarwal A, Emary PC, Gallo L, Oparin Y, Shin SH, Fitzcharles MA, Adachi JD, Cooper MD, Craigie S, Rai A, Wang L, Couban RJ, Busse JW. Physicians' knowledge, attitudes, and practices regarding fibromyalgia: A systematic review and meta-analysis of cross-sectional studies. Medicine (Baltimore). 2024 Aug 2;103(31):e39109. doi: 10.1097/MD.0000000000039109.
- Background: PubMed 35993085Ahmad M, Ahmed I, Jeon G. A sustainable advanced artificial intelligence-based framework for analysis of COVID-19 spread. Environ Dev Sustain. 2022 Aug 16:1-16. doi: 10.1007/s10668-022-02584-0. Online ahead of print.
- 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.
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 Fibromyalgia (FM) and Pain, run by Faculdade de Ciências Médicas de Minas Gerais at 1 site in Brazil.
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 1 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: looking for participants now, as of the sponsor's last update on 19 Nov 2025. 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 Brazil. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Alessandra H De Souza, PhD (55-31984205240, alessandra.souza@cienciasmedicasmg.edu.br), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Use the artificial intelligence tool to analyze the facial expression of patients with fibromyalgia in order to recognize pain. (time frame: The estimated time for the anamnesis is one hour, during which time biological samples will be taken and each patient's facial expressions will be recorded on camera.). 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 NCT06813352, which also lists 3 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 19 Nov 2025.