Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
NA
192 participants
INTERVENTIONAL
2025-10-15
2026-12-30
Brief Summary
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Detailed Description
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The 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.
Participants will be randomized into three groups:
RGS+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.
Conditions
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Keywords
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Study Design
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RANDOMIZED
PARALLEL
TREATMENT
DOUBLE
Study Groups
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RGS with AI-based Clinical Decision Support
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.
AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy
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.
RGS without AI-based Decision Support
Participants receive the same home-based RGS virtual reality rehabilitation, but exercise prescriptions are set and adjusted manually by clinicians without AI assistance.
AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy
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.
Control Group - Standard Care
Participants receive usual post-stroke rehabilitation services available at their site, without access to the RGS@home platform.
No interventions assigned to this group
Interventions
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AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy
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.
Eligibility Criteria
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Inclusion Criteria
* Patients presenting a first-ever ischemic or intracerebral hemorrhagic stroke
* 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).
* Age \> 18 years old
* Able to sit on a chair or a wheelchair and interact with RGS during an entire session
* Minimal experience with smartphone technology based on the clinician's opinion
* Willing to participate in the RGS therapy
* Sign the Informed Consent Form
Exclusion Criteria
* Severe cognitive capabilities preventing the execution of the experiment or according to clinicians' criteria.
* 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)
* Unable to use the RGS app independently according to the clinician's observations and lacking support from a caregiver to use the RGS app
* No experience with smartphone technology or based on the clinician's opinion.
* Refusal to sign the Informed Consent
* Participating or planning to participate in another trial while being part of the present study.
18 Years
ALL
No
Sponsors
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Universidad Miguel Hernandez de Elche
OTHER
Eodyne Systems SL
INDUSTRY
Responsible Party
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Locations
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CHU de Limoges
Limoges, , France
San Camillo Hospital, IRCCS
Venice, Veneto, Italy
UMF
Cluj-Napoca, , Romania
Parc Sanitari Sant Joan de Deu (SJDD)
Barcelona, , Spain
Countries
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Central Contacts
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Facility Contacts
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Stephane Mandigout
Role: primary
Francesca Burgio
Role: primary
Adina Dora Stan
Role: primary
Raffaele Fiorillo
Role: primary
References
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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.
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.
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.
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.
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.
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.
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.
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.
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.
Other Identifiers
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AISN-2025
Identifier Type: -
Identifier Source: org_study_id