[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100521740":3},{"organization":4,"armGroups":7,"interventions":18,"overallOfficials":23,"centralContacts":27,"locations":36,"responsibleParty":70,"collaborators":73,"id":93,"slug":94,"hasResults":95,"nctId":96,"briefTitle":97,"officialTitle":98,"acronym":99,"eligibilityCriteria":100,"healthyVolunteers":101,"sex":102,"minAge":103,"maxAge":104,"enrollmentInfo":105,"targetDuration":10,"studyType":108,"phases":10,"briefSummary":109,"conditions":110,"keywords":112,"overallStatus":125,"whyStopped":10,"lastUpdateSubmitDate":126,"lastUpdatePostDateStruct":127,"startDateStruct":130,"completionDateStruct":131,"leadSponsor":133,"locationsCount":134},{"fullName":5,"class":6},"IRCCS Fondazione Stella Maris","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Typically developing children",null,"Children aged 5 to 15 years old with no clinically documented disorders.",[13],"Other: Artificial Intelligence for combining multi-domain data acquisition",{"label":15,"type":10,"description":16,"interventionNames":17},"Children with Unilateral Cerebral Palsy","Children aged 5 to 15 years old with a diagnosis of Unilateral Cerebral Palsy",[13],[19],{"type":6,"name":20,"description":21,"armGroupLabels":22,"otherNames":10},"Artificial Intelligence for combining multi-domain data acquisition","Artificial Intelligence and machine learning techniques to combine data coming from multidomains data collection (such as clinical multiaxial assessments and questionnaires, Neuroimaging, Upper limb movement analysis during clinical assessment and daily life )",[15,9],[24],{"name":25,"affiliation":5,"role":26},"Giuseppina Sgandurra, Md, PhD","PRINCIPAL_INVESTIGATOR",[28,33],{"name":29,"role":30,"phone":31,"phoneExt":10,"email":32},"Giuseppina Sgandurra, PhD, MD","CONTACT","3392472874","g.sgandurra@fsm.unipi.it",{"name":34,"role":30,"phone":10,"phoneExt":10,"email":35},"Elena Beani, PhD","e.beani@fsm.unipi.it",[37,56],{"facility":5,"status":10,"city":38,"state":10,"zip":39,"country":40,"countryCode":41,"cosmosGeoPoint":42,"geoPoint":47,"contacts":48},"Pisa","56128","Italy","IT",{"type":43,"coordinates":44},"Point",[45,46],10.4036,43.70853,{"lat":46,"lon":45},[49,52,54],{"name":50,"role":30,"phone":31,"phoneExt":51,"email":32},"Giuseppina Sgandurra, MD, PhD","0039",{"name":34,"role":30,"phone":53,"phoneExt":51,"email":35},"3475823890",{"name":34,"role":55,"phone":10,"phoneExt":10,"email":10},"SUB_INVESTIGATOR",{"facility":57,"status":10,"city":58,"state":10,"zip":59,"country":60,"countryCode":61,"cosmosGeoPoint":62,"geoPoint":66,"contacts":67},"Universidad de Castilla - La Mancha","Toledo","45071","Spain","ES",{"type":43,"coordinates":63},[64,65],-4.02263,39.8581,{"lat":65,"lon":64},[68],{"name":69,"role":30,"phone":10,"phoneExt":10,"email":10},"Rocio Palomo Carrion",{"type":26,"investigatorFullName":71,"investigatorTitle":72,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"Giuseppina Sgandurra","MD, PhD",[74,76,78,81,83,85,87,89,91],{"name":75,"class":6},"University of Pisa",{"name":77,"class":6},"University of Castilla-La Mancha",{"name":79,"class":80},"Fight The Stroke","UNKNOWN",{"name":82,"class":6},"SCUOLA SUPERIORE DI STUDI UNIVERSITARI E DI PERFEZIONAMENTO S ANNA",{"name":84,"class":80},"Noldus Information Technology Bv",{"name":86,"class":80},"Khymeia",{"name":88,"class":80},"Tyromotion GMBH",{"name":90,"class":6},"The University of Queensland",{"name":92,"class":6},"University of Salento","100521740","validation-of-ai-for-personalized-assessment-and-rehabilitation-of-upper-limb-in-children-with-unilateral-cerebral-palsy-100521740",false,"NCT06073522","Validation of AI for Personalized Assessment and Rehabilitation of Upper Limb in Children With Unilateral Cerebral Palsy","Clinical Validation of Artificial INtelligence for Providing a Personalized Motor Clinical Profile Assessment and Rehabilitation of Upper Limb in Children With Unilateral Cerebral Palsy","AInCP","For the group of children with UCP:\n\nInclusion criteria\n\n* Children with confirmed diagnosis of UCP mainly spastic form\n* Ages from 5 to 15 years old\n* Manual ability levels from I to III in the Manual Ability Classification System (MACS) Exclusion criteria\n* Severe Upper Limb (UpL) impairment (MACS ≥ level IV: inability to grasp)\n* Botulinum toxin-A injections in UpL within 6 months prior to study entry\n* UpL surgery within 12 months prior to study entry\n* Severe comobordities and\u002For severe cognitive disability\n\nFor Typically developing children:\n\n* Ages from 5 to 15 years old\n* No documented clinically relevant disorders",true,"ALL","5 Years","15 Years",{"count":106,"type":107},500,"ESTIMATED","OBSERVATIONAL","Unilateral Cerebral palsy (UCP) is the most common neurological chronic disease in childhood with a significant burden on children, their families and health care system.\n\nAInCP aims to develop evidence-based clinical Decision Support Tools (DST) for personalized functional diagnosis, Upper Limb (UpL) assessment and home-based intervention for children with UCP, by developing, testing and validating trustworthy Artificial Intelligence (AI) and cost-effective strategies. The AInCP approach will: i) establish a clinical diagnosis and accurate prognosis for treatment response of individual UCP profiles, by employing a multimodal approach including clinical phenotyping, advanced brain imaging and real-life monitoring of UpL function, and ii) provide personalized home-based treatment, from advanced ICT and AI technologies.\n\nThe AInCP will build upon personalized diagnostic and rehabilitative DST (dDST and rDST) to be developed and validated through large observational and rehabilitation studies, including at least 200 and 150 children with UCP, respectively. Using data driven and AI approach, dDST and rDST will be combined for developing a theranostic DST (tDST) that will allow the re-designing of an economical, ethical, sustainable decision-making process for delivering a personalized and validated approach, focused on the care, monitoring and rehabilitation of UpL in children with UCP. AInCP is a significant example of a transdisciplinary approach, where all project collaborators (clinicians, data scientists, physicists, engineers, economists, ethicists, SMEs, children and parent associations) will work closely together in building the AInCP approach. This approach will, therefore, hinge on transdisciplinary contributions, multi- dimensional data, sets of innovative devices and fair AI-based algorithms, clinically effective and able to reduce users? and market barriers of acceptability, reimbursability and adoption of the proposed solution.",[111],"Unilateral Cerebral Palsy",[113,114,115,116,117,118,119,120,121,122,123,124],"Cerebral Palsy","Paediatric Stroke","Predictive Biomarkers","Brain structure","Upper limb assessment","Upper limb Rehabilitation","Machine Learning","Data science","Telerehabilitation","Multi agent systems","intelligent systems","Artificial intelligence","NOT_YET_RECRUITING","2023-10-07",{"date":128,"type":129},"2023-10-10","ACTUAL",{"date":128,"type":107},{"date":132,"type":107},"2027-06-30",{"name":5,"class":6},2]