Using Artificial Intelligence and Biomarkers to Analyze Facial Expressions for Pain Detection in Fibromyalgia Patients

What this Trial Is About

Fibromyalgia FM is a long-lasting condition causing widespread body pain, muscle tenderness, stiffness, fatigue, and sleep problems, which significantly affect quality of life. Because pain is subjective and hard to measure, this research aims to develop more objective ways to assess pain using facial expression analysis powered by artificial intelligence AI combined with molecular biomarkers. This study explores these new methods to better understand and quantify pain intensity in people with FM. The study observes two groups patients diagnosed with fibromyalgia and those without the condition. Facial expressions are recorded and analyzed by AI to identify pain-related patterns. Saliva samples are collected to examine molecular markers like inflammatory proteins and genes linked to FM. Participants also complete clinical questionnaires such as the Visual Analogue Scale and the Generalized Pain Index to validate findings. This combined approach hopes to improve pain assessment accuracy. Participants will be followed over several months during which their facial expressions and biological samples are collected for analysis. The AI tool is used to recognize pain intensity from facial cues, and molecular tests help identify markers associated with pain. Researchers will compare AI results with questionnaire scores and molecular findings. The main outcome is the AI-based facial pain recognition, supported by biochemical analysis of biomarkers. Overall, the study aims to advance personalized diagnosis and treatment for fibromyalgia patients.

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