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NCT Number: NCT07138495

Integrating AI in Stroke Neurorehabilitation

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.

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Key information

Conditions

Stroke Brain Diseases Cardiovascular Diseases Central Nervous System Diseases Cerebrovascular Disorders Nervous System Diseases Vascular Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

CHU de Limoges, Limoges, France

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About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

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

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.

Primary outcomes

  1. 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

Secondary outcomes

  1. Cognitive function change

    Time frame: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks

    Cognitive evaluation with TAP (alertness, sustained and divided attention, selective attention/flexibility, spatial attention, and working memory).

  2. Disability evaluation

    Time frame: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks

    Assessment of global disability with the Modified Ranking Scale - mRS

  3. Emotional change

    Time frame: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks

    Assessed with the Hamilton Depression Scale

  4. Quality of life and Health status

    Time frame: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks

    Assessed with EQ-5D-5L questionnaire

  5. Therapists' qualitative evaluation of the AI-based decision support system performance

    Time frame: At the end of the study, at 20 weeks.

    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

Other outcomes

  1. RGS intrinsic measures change

    Time frame: At enrollment, 2, 4, 8 weeks, end of treatment (12 weeks), and follow-up (20 weeks)

    RGS intrinsic measures, i.e., exercise difficulty settings and kinematics RGS protocols for motor and cognitive assessment

Study contacts

Contact information is provided by the study sponsor or research team.

Anna Mura

CONTACT

[email protected]

Sponsor

CONTACT

[email protected]

+34 931389642

Sponsors and collaborators

Lead sponsor

Eodyne Systems SL

Industry

Collaborators

  • Universidad Miguel Hernandez de Elche

Registry information

Official study title

Integrating AI in Stroke Neurorehabilitation (AISN)

Acronym: AISN

Important dates

Study start
2025
Primary completion
2026
Study completion
2026
First posted
Aug 22, 2025
Registry last updated
Dec 22, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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