Refining multiple AI strategies for automatic pain assessment (RUGGI)
Refining mUltiple Artificial intelliGence strateGies for Automatic Pain Assessment Investigations: RUGGI Study
This project tests whether AI models using wearable sensors, facial video/thermography, and physiological signals can detect and estimate pain in adults with chronic or cancer-related pain.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 200 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Azienda Ospedaliera OO.RR. S. Giovanni di Dio e Ruggi D'Aragona Academic / other |
| Locations | 1 site (Salerno, Italy) |
| Trial ID | NCT07038434 on ClinicalTrials.gov |
What this trial studies
This single-center, observational-interventional project will enroll about 200 adults with chronic pain from oncologic and non-oncologic causes and collect multimodal, non-invasive data including EEG, HRV, GSR/EDA, EMG, PPG, infrared thermography, facial video, and self-report questionnaires. Recordings occur at structured timepoints (baseline rest, during a Stroop task, and follow-up) with wearable sensors and synchronized video to capture physiological and behavioral responses. Data will be preprocessed, features extracted, and machine learning pipelines (SVMs, random forests, CNNs, YOLO, MLPs) trained with cross-validation and grid-search optimization to recognize presence and severity of pain. The project also intends to produce a standardized, anonymized APA dataset and explore links between objective signals, treatment response, and quality of life.
Who should consider this trial
Good fit: Adults (≥18) with chronic primary, secondary non-cancer, or cancer-related pain per IASP/ICD-11 criteria who can understand procedures, consent, and attend onsite recording sessions are ideal candidates.
Not a fit: People on psychotropic medications or with active psychiatric disorders, substance abuse, pregnancy, cognitive impairment, or those unable to travel to the study site are excluded and unlikely to benefit from participation.
Why it matters
Potential benefit: If successful, the approach could give clinicians more objective, continuous information about pain to help tailor treatments and reduce under- or over-treatment.
How similar studies have performed: Prior work using facial expressions and physiological signals for pain detection has shown promising but inconsistent results, and fully validated multimodal AI models for chronic pain remain limited.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Adults (≥18 years old) with chronic pain, defined according to IASP and ICD-11 as pain that persists or recurs for more than three months. * Diagnosed with either: * Chronic primary pain (e.g., fibromyalgia, irritable bowel syndrome, chronic headaches) * Chronic secondary non-cancer pain (e.g., low back pain, osteoarthritis, post-surgical pain) * Chronic cancer-related pain (due to cancer or its treatment) * Ability to understand the study procedures and provide written informed consent. Exclusion Criteria: * Current treatment with psychotropic drugs or presence of active psychiatric disorders (e.g., psychosis, major depression). * Known history of alcohol or substance abuse. * Pregnancy or breastfeeding. * Age under 18 years. * Inability to provide informed consent (e.g., due to cognitive impairment).
Where this trial is running
Salerno, Italy
- Azienda Ospedaliera Universitaria San Giovanni di Dio e Ruggi d'Aragona — Salerno, Italy, Italy (Recruiting)
Study contacts
- Principal investigator: Marco Cascella, MD, PhD — University of Salerno
- Study coordinator: Marco Cascella, MD, PhD
- Email: mcascella@unisa.it
- Phone: +39 089 672428
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.