[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100595898":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":23,"centralContacts":28,"locations":37,"responsibleParty":71,"collaborators":74,"id":80,"slug":81,"hasResults":82,"nctId":83,"briefTitle":84,"officialTitle":84,"acronym":85,"eligibilityCriteria":86,"healthyVolunteers":82,"sex":87,"minAge":88,"maxAge":32,"enrollmentInfo":89,"targetDuration":32,"studyType":92,"phases":93,"briefSummary":95,"conditions":96,"keywords":101,"overallStatus":40,"whyStopped":32,"lastUpdateSubmitDate":109,"lastUpdatePostDateStruct":110,"startDateStruct":113,"completionDateStruct":115,"leadSponsor":117,"locationsCount":118},{"fullName":5,"class":6},"Azienda Ospedaliera OO.RR. S. Giovanni di Dio e Ruggi D'Aragona","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"AI-Based Pain Assessment in Chronic Pain Patients","EXPERIMENTAL","Participants with chronic pain will undergo a multimodal, non-invasive diagnostic assessment including self-reported pain questionnaires (NRS, DN-4, BPI), wearable biosignal acquisition (EEG, EMG, EDA, HRV), facial thermography using the HIRA system, video-based facial expression analysis, linguistic evaluation, and the Stroop Test. These data will be used to develop and validate machine learning models for automatic pain assessment.",[13],"Diagnostic Test: Multimodal AI-Based Pain Assessment",[15],{"type":16,"name":17,"description":18,"armGroupLabels":19,"otherNames":20},"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.",[9],[21,22],"Automatic Pain Assessment","AI Pain Evaluation",[24],{"name":25,"affiliation":26,"role":27},"Marco Cascella, MD, PhD","University of Salerno","PRINCIPAL_INVESTIGATOR",[29,34],{"name":25,"role":30,"phone":31,"phoneExt":32,"email":33},"CONTACT","+39 089 672428",null,"mcascella@unisa.it",{"name":35,"role":30,"phone":32,"phoneExt":32,"email":36},"Valentina Cerrone, RN, MSc","valentina.cerrone@sangiovannieruggi.it",[38],{"facility":39,"status":40,"city":41,"state":42,"zip":43,"country":42,"countryCode":44,"cosmosGeoPoint":45,"geoPoint":50,"contacts":51},"Azienda Ospedaliera Universitaria San Giovanni di Dio e Ruggi d'Aragona","RECRUITING","Salerno","Italy","84131","IT",{"type":46,"coordinates":47},"Point",[48,49],14.79328,40.67545,{"lat":49,"lon":48},[52,54,55,56,59,61,63,65,67,69],{"name":25,"role":30,"phone":53,"phoneExt":32,"email":33},"+39 089672428",{"name":35,"role":30,"phone":32,"phoneExt":32,"email":36},{"name":25,"role":27,"phone":32,"phoneExt":32,"email":32},{"name":57,"role":58,"phone":32,"phoneExt":32,"email":32},"Valentina Cerrone","SUB_INVESTIGATOR",{"name":60,"role":58,"phone":32,"phoneExt":32,"email":32},"Giuseppe Polese",{"name":62,"role":58,"phone":32,"phoneExt":32,"email":32},"Ornella Piazza",{"name":64,"role":58,"phone":32,"phoneExt":32,"email":32},"Francesco Amato",{"name":66,"role":58,"phone":32,"phoneExt":32,"email":32},"Maria Romano",{"name":68,"role":58,"phone":32,"phoneExt":32,"email":32},"Alfonso Maria Ponsiglione",{"name":70,"role":58,"phone":32,"phoneExt":32,"email":32},"Francesco Di Salle",{"type":72,"investigatorFullName":57,"investigatorTitle":73,"investigatorAffiliation":5,"oldNameTitle":32,"oldOrganization":32},"SPONSOR_INVESTIGATOR","Study Coordinator",[75,78],{"name":76,"class":77},"University of Salerno, Italy","UNKNOWN",{"name":79,"class":6},"Federico II University","100595898","refining-multiple-artificial-intelligence-strategies-for-automatic-pain-assessment-investigations-ruggi-study-100595898",false,"NCT07038434","Refining mUltiple Artificial intelliGence strateGies for Automatic Pain Assessment Investigations: RUGGI Study","RUGGI","Inclusion Criteria:\n\n* 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.\n* Diagnosed with either:\n* Chronic primary pain (e.g., fibromyalgia, irritable bowel syndrome, chronic headaches)\n* Chronic secondary non-cancer pain (e.g., low back pain, osteoarthritis, post-surgical pain)\n* Chronic cancer-related pain (due to cancer or its treatment)\n* Ability to understand the study procedures and provide written informed consent.\n\nExclusion Criteria:\n\n* Current treatment with psychotropic drugs or presence of active psychiatric disorders (e.g., psychosis, major depression).\n* Known history of alcohol or substance abuse.\n* Pregnancy or breastfeeding.\n* Age under 18 years.\n* Inability to provide informed consent (e.g., due to cognitive impairment).","ALL","18 Years",{"count":90,"type":91},200,"ESTIMATED","INTERVENTIONAL",[94],"NA","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.\n\nThe 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.\n\nAll 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.",[97,98,99,100],"Chronic Pain","Cancer Pain","Neuropathic Pain","Pain Assessment",[102,103,104,21,105,106,107,108,97],"Artificial Intelligence","Machine Learning","Deep Learning","Facial Expression Analysis","Natural Language Processing","Stroop Test","Bio-signals","2025-06-17",{"date":111,"type":112},"2025-06-26","ACTUAL",{"date":114,"type":112},"2025-05-06",{"date":116,"type":91},"2026-01",{"name":57,"class":6},1]