Integrating AI in Stroke Neurorehabilitation

NCT ID: NCT07138495

Last Updated: 2025-12-22

Study Results

Results pending

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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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

192 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-10-15

Study Completion Date

2026-12-30

Brief Summary

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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.

Detailed Description

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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.

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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Stroke

Keywords

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Stroke home based rehabilitation digital health virtual reality personalized rehabilitation

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

TREATMENT

Blinding Strategy

DOUBLE

Participants Outcome Assessors

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.

Group Type EXPERIMENTAL

AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy

Intervention Type DEVICE

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.

Group Type ACTIVE_COMPARATOR

AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy

Intervention Type DEVICE

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.

Group Type NO_INTERVENTION

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.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* ≥ 6 months post-stroke
* 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

* Diagnosis with Epilepsy
* 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.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Universidad Miguel Hernandez de Elche

OTHER

Sponsor Role collaborator

Eodyne Systems SL

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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CHU de Limoges

Limoges, , France

Site Status NOT_YET_RECRUITING

San Camillo Hospital, IRCCS

Venice, Veneto, Italy

Site Status RECRUITING

UMF

Cluj-Napoca, , Romania

Site Status RECRUITING

Parc Sanitari Sant Joan de Deu (SJDD)

Barcelona, , Spain

Site Status NOT_YET_RECRUITING

Countries

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France Italy Romania Spain

Central Contacts

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Sponsor

Role: CONTACT

Phone: +34 931389642

Email: [email protected]

Anna Mura

Role: CONTACT

Email: [email protected]

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.

Reference Type BACKGROUND
PMID: 16813784 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 18760153 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 19228851 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 34972526 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 20860808 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 33349012 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 32143674 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 20332511 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 31920570 (View on PubMed)

Other Identifiers

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AISN-2025

Identifier Type: -

Identifier Source: org_study_id