Refining mUltiple Artificial intelliGence strateGies for Automatic Pain Assessment Investigations: RUGGI Study
NCT07038434 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 200
Last updated 2025-06-26
Summary
This single-center, non-profit, observational-interventional study aims to develop artificial intelligence (AI) models for the automatic assessment of chronic pain (APA - Automatic Pain Assessment). The study will enroll adult patients with chronic pain of various origins (oncologic and non-oncologic). Participants will undergo multidimensional evaluations that include clinical assessments, self-report questionnaires, bio-signal collection (e.g., EEG, EDA, HRV, GSR, PPG), and facial expression analysis via infrared thermography and video recordings.
The primary objective is to calibrate and test machine learning and deep learning models to recognize and predict the presence and severity of pain using multimodal data inputs. Secondary objectives include evaluating the effectiveness of pain treatments, assessing quality of life, and developing a standardized APA dataset for future research.
All data collection procedures are non-invasive and safe, and include tools like wearable sensors and standardized neurocognitive tests. The study is approved by the Italian Ethics Committee (Comitato Etico Territoriale Campania 2) and complies with GDPR and EU AI regulations.
Conditions
- Chronic Pain
- Cancer Pain
- Neuropathic Pain
- Pain Assessment
Interventions
- DIAGNOSTIC_TEST
-
Multimodal AI-Based Pain Assessment
A non-invasive, multimodal diagnostic procedure combining self-reported pain scales (NRS, DN-4, BPI), wearable biosignal acquisition (EDA, EMG, HRV, EEG), facial thermography (HIRA system), video-based facial expression analysis, linguistic interview, and the Stroop Test. Data are used to train and validate machine learning models for automatic pain assessment in chronic pain patients.
Sponsors & Collaborators
-
University of Salerno, Italy
collaborator UNKNOWN -
Federico II University
collaborator OTHER -
Valentina Cerrone
lead OTHER
Principal Investigators
-
Marco Cascella, MD, PhD · University of Salerno
Study Design
- Allocation
- NA
- Purpose
- DIAGNOSTIC
- Masking
- NONE
- Model
- SINGLE_GROUP
Eligibility
- Min Age
- 18 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2025-05-06
- Primary Completion
- 2025-12-31
- Completion
- 2026-01-31
Countries
- Italy
Study Locations
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