StrokeAISNNCT07138495
Integrating AI in Stroke Neurorehabilitation
A study testing AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy in people with Stroke, run by Eodyne Systems SL at 4 sites in 4 countries.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Stroke
- What is being tested?
- AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 192 participants
- Where
- 4 sitesin 4 countries
- Study dates
- 15 Oct 2025to 30 Dec 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- ≥ 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
Who cannot join
- 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.
Trial locations and contacts
4 sites in 4 countries. Contact the study team or a site near you to ask about taking part.
Anna Mura contact
4 sites in 4 countries
France1 site, 1 recruiting
- Not yet recruiting
CHU de Limoges
Limoges
Stephane Mandigout, +33 (0)5 55 45 76 32, stephane.mandigout@unilim.fr
Italy1 site, 1 recruiting
- Recruiting
San Camillo Hospital, IRCCS
Venice, Veneto, 30126
Francesca Burgio, +39 0412207536, francesca.burgio@hsancamillo.it
Romania1 site, 1 recruiting
- Recruiting
UMF
Cluj-Napoca
Adina Dora Stan, +40 0264593884, adinadora@elearn.umfcluj.ro
Spain1 site, 1 recruiting
- Not yet recruiting
Parc Sanitari Sant Joan de Deu (SJDD)
Barcelona
Raffaele Fiorillo, +34 936 406 350, raffaele.fiorillo@sjd.es
About this study
Official title: Integrating AI in Stroke Neurorehabilitation (AISN)
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.
Read the detailed description
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
- Stroke
- Being tested
- AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy
- Keywords
- Stroke, home based rehabilitation, digital health, virtual reality, personalized rehabilitation
- Medical subject headings
- Stroke
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapyDevice
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.
| Study group | Role | What they receive |
|---|---|---|
| RGS with AI-based Clinical Decision Support | Experimental | 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. Receives: Device: AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy |
| RGS without AI-based Decision Support | Active comparator | Participants receive the same home-based RGS virtual reality rehabilitation, but exercise prescriptions are set and adjusted manually by clinicians without AI assistance. Receives: Device: AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy |
| Control Group - Standard Care | No intervention | Participants receive usual post-stroke rehabilitation services available at their site, without access to the RGS@home platform. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Upper limb motor change
Evaluation with the ARAT scale
Measured: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks
Secondary outcomes (5)
Cognitive function change
Cognitive evaluation with TAP (alertness, sustained and divided attention, selective attention/flexibility, spatial attention, and working memory).
Measured: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks
Disability evaluation
Assessment of global disability with the Modified Ranking Scale - mRS
Measured: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks
Emotional change
Assessed with the Hamilton Depression Scale
Measured: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks
Quality of life and Health status
Assessed with EQ-5D-5L questionnaire
Measured: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks
Therapists' qualitative evaluation of the AI-based decision support system performance
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
Measured: At the end of the study, at 20 weeks.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Aug 2025
- Study start15 Oct 2025
- Primary completion30 Dec 2026 (estimated)
- Study completion30 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (9)Papers the sponsor has linked to this study.
- Other trials for StrokeStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Participant, Outcomes assessor
- Enrolment
- 192 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Eodyne Systems SL
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Universidad Miguel Hernandez de Elche
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07138495
- Sponsor's protocol ID
- AISN-2025
- Acronym
- AISN
- Status last verified
- Dec 2025
- First submitted
- 14 Aug 2025
- Last updated
- 22 Dec 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: 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.
Publications
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.
PubMed 16813784Lang 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.
PubMed 18760153Hsieh 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.
PubMed 19228851Ballester 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.
PubMed 34972526Cameirao 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.
PubMed 20860808Duncan 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.
PubMed 33349012Maier 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.
PubMed 32143674Moher 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.
PubMed 20332511Maier 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.
PubMed 31920570
Study at a glance
From the registry record, last updated by the sponsor on 22 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Integrating AI in Stroke Neurorehabilitation (AISN)
- ClinicalTrials.gov ID
- NCT07138495
- Acronym / sponsor ID
- AISN / AISN-2025
- Conditions
- Stroke
- Keywords
- Stroke, home based rehabilitation, digital health, virtual reality, personalized rehabilitation
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 192 participants (estimated)
- Lead sponsor
- Eodyne Systems SLIndustry (pharma, biotech, devices)
- Collaborators
- Universidad Miguel Hernandez de Elche
- Study start
- 15 Oct 2025 (actual)
- Primary completion
- 30 Dec 2026 (estimated)
- Study completion
- 30 Dec 2026 (estimated)
- First posted
- 22 Aug 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
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.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, outcomes assessor)
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| RGS with AI-based Clinical Decision Support | Experimental | Device: AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapyParticipants 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. |
| RGS without AI-based Decision Support | Active comparator | Device: AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapyParticipants receive the same home-based RGS virtual reality rehabilitation, but exercise prescriptions are set and adjusted manually by clinicians without AI assistance. |
| Control Group - Standard Care | No intervention | –Participants receive usual post-stroke rehabilitation services available at their site, without access to the RGS@home platform. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (8 listed)
- ≥ 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
Key exclusion criteria (7 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapyThe 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. | Device | RGS with AI-based Clinical Decision Support, RGS without AI-based Decision Support |
Primary outcome
Upper limb motor change
Time frame: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks
Evaluation with the ARAT scale
5 secondary outcomes
Cognitive function change
Time frame: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks
Disability evaluation
Time frame: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks
Emotional change
Time frame: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks
Quality of life and Health status
Time frame: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks
Therapists' qualitative evaluation of the AI-based decision support system performance
Time frame: At the end of the study, at 20 weeks.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 22 Dec 2025.
- Background: PubMed 16813784Rabadi 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.
- Background: PubMed 18760153Lang 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.
- Background: PubMed 19228851Hsieh 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.
- Background: PubMed 34972526Ballester 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.
- Background: PubMed 20860808Cameirao 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.
- Background: PubMed 33349012Duncan 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.
- Background: PubMed 32143674Maier 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.
- Background: PubMed 20332511Moher 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.
- Background: PubMed 31920570Maier 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.
- Individual participant dataSharing planned: No. 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Anna Mura contact
4 sites in 4 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-personalized virtual reality rehabilitation system for unsupervised home-based stroke therapy in people with Stroke, run by Eodyne Systems SL at 4 sites in 4 countries.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 8 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 22 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 4 sites in France, Italy, Romania, Spain. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Sponsor (+34 931389642, contact@eodyne.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Upper limb motor change (time frame: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07138495, which also lists 9 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 22 Dec 2025.