Ignite Creation Date:
2025-12-24 @ 2:12 PM
Ignite Modification Date:
2025-12-24 @ 2:12 PM
Study NCT ID:
NCT07138495
Status:
RECRUITING
Last Update Posted:
2025-12-22
First Post:
2025-08-14
Is Possible Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Integrating AI in Stroke Neurorehabilitation
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D020521', 'term': 'Stroke'}], 'ancestors': [{'id': 'D002561', 'term': 'Cerebrovascular Disorders'}, {'id': 'D001927', 'term': 'Brain Diseases'}, {'id': 'D002493', 'term': 'Central Nervous System Diseases'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}, {'id': 'D014652', 'term': 'Vascular Diseases'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'DOUBLE', 'whoMasked': ['PARTICIPANT', 'OUTCOMES_ASSESSOR']}, 'primaryPurpose': 'TREATMENT', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 192}}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2025-10-15', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-12', 'completionDateStruct': {'date': '2026-12-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-12-16', 'studyFirstSubmitDate': '2025-08-14', 'studyFirstSubmitQcDate': '2025-08-21', 'lastUpdatePostDateStruct': {'date': '2025-12-22', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-08-22', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-12-30', 'type': 'ESTIMATED'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'RGS intrinsic measures change', 'timeFrame': 'At enrollment, 2, 4, 8 weeks, end of treatment (12 weeks), and follow-up (20 weeks)', 'description': 'RGS intrinsic measures, i.e., exercise difficulty settings and kinematics RGS protocols for motor and cognitive assessment'}], 'primaryOutcomes': [{'measure': 'Upper limb motor change', 'timeFrame': 'From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks', 'description': 'Evaluation with the ARAT scale'}], 'secondaryOutcomes': [{'measure': 'Cognitive function change', 'timeFrame': 'From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks', 'description': 'Cognitive evaluation with TAP (alertness, sustained and divided attention, selective attention/flexibility, spatial attention, and working memory).'}, {'measure': 'Disability evaluation', 'timeFrame': 'From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks', 'description': 'Assessment of global disability with the Modified Ranking Scale - mRS'}, {'measure': 'Emotional change', 'timeFrame': 'From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks', 'description': 'Assessed with the Hamilton Depression Scale'}, {'measure': 'Quality of life and Health status', 'timeFrame': 'From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks', 'description': 'Assessed with EQ-5D-5L questionnaire'}, {'measure': "Therapists' qualitative evaluation of the AI-based decision support system performance", 'timeFrame': 'At the end of the study, at 20 weeks.', 'description': 'Usability (standardized questionnaire on usage, credibility, and time consumption) Cost efficiency (between the two experimental groups RGS+AI/-AI, time spent for making the prescription, technical support, patient visits during therapy) RGS +AI/-AI performance (pre- and post-treatment values of diagnostics, prognostics, recommendations, and deviations'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Stroke', 'home based rehabilitation', 'digital health', 'virtual reality', 'personalized rehabilitation'], 'conditions': ['Stroke']}, 'referencesModule': {'references': [{'pmid': '16813784', 'type': 'BACKGROUND', 'citation': 'Rabadi MH, Rabadi FM. Comparison of the action research arm test and the Fugl-Meyer assessment as measures of upper-extremity motor weakness after stroke. Arch Phys Med Rehabil. 2006 Jul;87(7):962-6. doi: 10.1016/j.apmr.2006.02.036.'}, {'pmid': '18760153', 'type': 'BACKGROUND', 'citation': 'Lang CE, Edwards DF, Birkenmeier RL, Dromerick AW. Estimating minimal clinically important differences of upper-extremity measures early after stroke. Arch Phys Med Rehabil. 2008 Sep;89(9):1693-700. doi: 10.1016/j.apmr.2008.02.022.'}, {'pmid': '19228851', 'type': 'BACKGROUND', 'citation': 'Hsieh YW, Wu CY, Lin KC, Chang YF, Chen CL, Liu JS. Responsiveness and validity of three outcome measures of motor function after stroke rehabilitation. Stroke. 2009 Apr;40(4):1386-91. doi: 10.1161/STROKEAHA.108.530584. Epub 2009 Feb 19.'}, {'pmid': '34972526', 'type': 'BACKGROUND', 'citation': 'Ballester BR, Antenucci F, Maier M, Coolen ACC, Verschure PFMJ. Estimating upper-extremity function from kinematics in stroke patients following goal-oriented computer-based training. J Neuroeng Rehabil. 2021 Dec 31;18(1):186. doi: 10.1186/s12984-021-00971-8.'}, {'pmid': '20860808', 'type': 'BACKGROUND', 'citation': 'Cameirao MS, Badia SB, Oller ED, Verschure PF. Neurorehabilitation using the virtual reality based Rehabilitation Gaming System: methodology, design, psychometrics, usability and validation. J Neuroeng Rehabil. 2010 Sep 22;7:48. doi: 10.1186/1743-0003-7-48.'}, {'pmid': '33349012', 'type': 'BACKGROUND', 'citation': 'Duncan PW, Bushnell C, Sissine M, Coleman S, Lutz BJ, Johnson AM, Radman M, Pvru Bettger J, Zorowitz RD, Stein J. Comprehensive Stroke Care and Outcomes: Time for a Paradigm Shift. Stroke. 2021 Jan;52(1):385-393. doi: 10.1161/STROKEAHA.120.029678. Epub 2020 Dec 22.'}, {'pmid': '32143674', 'type': 'BACKGROUND', 'citation': 'Maier M, Ballester BR, Leiva Banuelos N, Duarte Oller E, Verschure PFMJ. Adaptive conjunctive cognitive training (ACCT) in virtual reality for chronic stroke patients: a randomized controlled pilot trial. J Neuroeng Rehabil. 2020 Mar 6;17(1):42. doi: 10.1186/s12984-020-0652-3.'}, {'pmid': '20332511', 'type': 'BACKGROUND', 'citation': 'Moher D, Hopewell S, Schulz KF, Montori V, Gotzsche PC, Devereaux PJ, Elbourne D, Egger M, Altman DG. CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials. BMJ. 2010 Mar 23;340:c869. doi: 10.1136/bmj.c869. No abstract available.'}, {'pmid': '31920570', 'type': 'BACKGROUND', 'citation': 'Maier M, Ballester BR, Verschure PFMJ. Principles of Neurorehabilitation After Stroke Based on Motor Learning and Brain Plasticity Mechanisms. Front Syst Neurosci. 2019 Dec 17;13:74. doi: 10.3389/fnsys.2019.00074. eCollection 2019.'}]}, 'descriptionModule': {'briefSummary': 'The AISN multicenter randomized controlled trial will assess the effectiveness of a novel artificial intelligence (AI)-based clinical decision-support system integrated into the Rehabilitation Gaming System (RGS) for home-based post-stroke rehabilitation. Approximately 192 participants ≥6 months post-stroke will be recruited across several European centers and assigned to one of three groups: RGS with AI decision support, RGS without AI, or standard care. The primary outcome is upper limb motor improvement for stroke patients, with secondary measures including cognitive function, independence, quality of life, usability, cost-effectiveness, and AI-based support performance.', 'detailedDescription': "The AISN study addresses the gap in long-term, personalized stroke rehabilitation after hospital discharge by evaluating an enhanced digital therapy platform that combines the clinically validated Rehabilitation Gaming System (RGS) with a newly developed AI-based decision-support module. This AI component analyzes patient performance data to provide clinicians with diagnostic and prognostic insights, along with tailored exercise prescriptions.\n\nThe trial's key innovation is the formal validation of the AI module in real-world clinical settings, assessing its concordance with clinician decisions, predictive accuracy, and contribution to patient outcomes.\n\nParticipants will be randomized into three groups:\n\nRGS+AI: Home-based RGS therapy with AI-driven recommendations for clinicians. RGS-AI: Home-based RGS therapy without AI support. Control: Standard rehabilitation care. The intervention phase will last 12 weeks, with daily home training for experimental groups, and follow-up at 20 weeks. In addition to standard clinical endpoints, the study will include predefined AI validation metrics, focusing on its potential as a certified medical device tool for scalable, personalized rehabilitation delivery."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': "Inclusion Criteria\n\n* ≥ 6 months post-stroke\n* Patients presenting a first-ever ischemic or intracerebral hemorrhagic stroke\n* Mild to Moderate unilateral upper limb motor impairment: Medical Research Council proximal and distal upper limb MRC ≥2; Action Research Arm Test: ARAT score \\< 50 (0 = no function, 57 = no functional limitation).\n* Age \\> 18 years old\n* Able to sit on a chair or a wheelchair and interact with RGS during an entire session\n* Minimal experience with smartphone technology based on the clinician's opinion\n* Willing to participate in the RGS therapy\n* Sign the Informed Consent Form\n\nExclusion Criteria\n\n* Diagnosis with Epilepsy\n* Severe cognitive capabilities preventing the execution of the experiment or according to clinicians' criteria.\n* Severe associated impairment such as proximal but not distal spasticity, communication disabilities (sensory, Wernicke aphasia or apraxia), major pain (VAS \\> 75-100 mm), orthopedic devices that would interfere with the correct execution of the experiment (Modified Ashworth Scale \\> 3)\n* Unable to use the RGS app independently according to the clinician's observations and lacking support from a caregiver to use the RGS app\n* No experience with smartphone technology or based on the clinician's opinion.\n* Refusal to sign the Informed Consent\n* Participating or planning to participate in another trial while being part of the present study."}, 'identificationModule': {'nctId': 'NCT07138495', 'acronym': 'AISN', 'briefTitle': 'Integrating AI in Stroke Neurorehabilitation', 'organization': {'class': 'INDUSTRY', 'fullName': 'Eodyne Systems SL'}, 'officialTitle': 'Integrating AI in Stroke Neurorehabilitation (AISN)', 'orgStudyIdInfo': {'id': 'AISN-2025'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'RGS with AI-based Clinical Decision Support', 'description': 'Participants receive home-based virtual reality rehabilitation using the Rehabilitation Gaming System (RGS@home), with exercise prescriptions personalized by an AI-driven clinical decision support system. Clinicians can review and adjust these prescriptions remotely.', 'interventionNames': ['Device: AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy']}, {'type': 'ACTIVE_COMPARATOR', 'label': 'RGS without AI-based Decision Support', 'description': 'Participants receive the same home-based RGS virtual reality rehabilitation, but exercise prescriptions are set and adjusted manually by clinicians without AI assistance.', 'interventionNames': ['Device: AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy']}, {'type': 'NO_INTERVENTION', 'label': 'Control Group - Standard Care', 'description': 'Participants receive usual post-stroke rehabilitation services available at their site, without access to the RGS@home platform.'}], 'interventions': [{'name': 'AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy', 'type': 'DEVICE', 'description': 'The personalized RGS app rehabilitation is a home-based, virtual reality therapy platform for motor and cognitive stroke recovery. Therapy tasks are gamified, task-specific, and adapt in difficulty based on real-time performance. An AI-driven clinical decision support system personalizes and updates exercise prescriptions after each session, with optional clinician adjustments. Integrated wearable sensors (RGSwear) track real-world activity and adherence. Data are securely uploaded to a cloud-based platform for remote monitoring. This is the first multicenter, international RCT to test AI-personalized VR rehabilitation at home with up to 12-month follow-up, combined with cost-effectiveness and usability evaluation.', 'armGroupLabels': ['RGS with AI-based Clinical Decision Support', 'RGS without AI-based Decision Support']}]}, 'contactsLocationsModule': {'locations': [{'city': 'Limoges', 'status': 'NOT_YET_RECRUITING', 'country': 'France', 'contacts': [{'name': 'Stephane Mandigout', 'role': 'CONTACT', 'email': 'stephane.mandigout@unilim.fr', 'phone': '+33 (0)5 55 45 76 32'}], 'facility': 'CHU de Limoges', 'geoPoint': {'lat': 45.83362, 'lon': 1.24759}}, {'zip': '30126', 'city': 'Venice', 'state': 'Veneto', 'status': 'RECRUITING', 'country': 'Italy', 'contacts': [{'name': 'Francesca Burgio', 'role': 'CONTACT', 'email': 'francesca.burgio@hsancamillo.it', 'phone': '+39 0412207536'}], 'facility': 'San Camillo Hospital, IRCCS', 'geoPoint': {'lat': 45.43713, 'lon': 12.33265}}, {'city': 'Cluj-Napoca', 'status': 'RECRUITING', 'country': 'Romania', 'contacts': [{'name': 'Adina Dora Stan', 'role': 'CONTACT', 'email': 'adinadora@elearn.umfcluj.ro', 'phone': '+40 0264593884'}], 'facility': 'UMF', 'geoPoint': {'lat': 46.76667, 'lon': 23.6}}, {'city': 'Barcelona', 'status': 'NOT_YET_RECRUITING', 'country': 'Spain', 'contacts': [{'name': 'Raffaele Fiorillo', 'role': 'CONTACT', 'email': 'raffaele.fiorillo@sjd.es', 'phone': '+34 936 406 350'}], 'facility': 'Parc Sanitari Sant Joan de Deu (SJDD)', 'geoPoint': {'lat': 41.38879, 'lon': 2.15899}}], 'centralContacts': [{'name': 'Sponsor', 'role': 'CONTACT', 'email': 'contact@eodyne.com', 'phone': '+34 931389642'}, {'name': 'Anna Mura', 'role': 'CONTACT', 'email': 'anna3.mura@gmail.com'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'No Individual participant data (IPD) will be shared. Only aggregated results or fully de-identified datasets may be provided to external researchers to ensure transparency while protecting confidentiality.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Eodyne Systems SL', 'class': 'INDUSTRY'}, 'collaborators': [{'name': 'Universidad Miguel Hernandez de Elche', 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR'}}}}