Analysis of Facial Expressions for Pain Recognition in Fibromyalgia: Using Artificial Intelligence and Biomarkers

NCT06813352 | Recruiting DMC

• 1 other identifier: CMMG
• Study Type: observational
• Target: 122
• Locations: 1 country
• Sites: 1

Brief 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. 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.

Conditions

Fibromyalgia (FM); Pain; Catastrophizing Pain

Keywords

Fibromyalgia; Artificial intelligence; Molecular biomarkers; Catastrophism; Facial expression

Outcome Measures

Primary Outcomes (1)

• 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.

  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.

  Estimated collection and analysis time: 5 hours of durability

Study Arms (2)

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.

Eligibility Criteria

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

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.

Sponsors & Collaborators

• Faculdade de Ciências Médicas de Minas Gerais: lead
• Fundação de Amparo à Pesquisa do estado de Minas Gerais: collaborator
• Conselho Nacional de Desenvolvimento Científico e Tecnológico: collaborator

Study Sites (1)

Outpatient Faculty Medical Sciences

Belo Horizonte, Minas Gerais, 30130110, Brazil

RECRUITING

Related Publications (3)

• 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.

  PMID: 34954186 BACKGROUND

• Agarwal 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.

  PMID: 39093781 BACKGROUND

• Ahmad 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.

  PMID: 35993085 BACKGROUND

Biospecimen

Retention: SAMPLES WITH DNA

Biological samples of saliva.

MeSH Terms

Conditions

Fibromyalgia; Pain; Facial Expression

Condition Hierarchy (Ancestors)

Muscular Diseases; Musculoskeletal Diseases; Rheumatic Diseases; Neuromuscular Diseases; Nervous System Diseases; Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Nonverbal Communication; Communication; Behavior

Central Study Contacts

Alessandra H De Souza, PhD

CONTACT

55-31984205240; alessandra.souza@cienciasmedicasmg.edu.br

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Target Duration: 1 Day
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Main supervisor of the study, statistical analyst and specialist in pain studies; pHd IN Pharmacological Sciences

Study Record Dates

• First Submitted: December 19, 2024
• First Posted: February 6, 2025
• Study Start: November 17, 2025
• Primary Completion: February 1, 2026
• Study Completion (Estimated): September 1, 2026
• Last Updated: November 19, 2025

Record last verified: 2025-02

Locations

BR (1)