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.
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 Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
DOUBLE
Enrollment
192
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.
CHU de Limoges
Limoges, France
NOT_YET_RECRUITINGSan Camillo Hospital, IRCCS
Venice, Veneto, Italy
RECRUITINGUMF
Cluj-Napoca, Romania
RECRUITINGParc Sanitari Sant Joan de Deu (SJDD)
Barcelona, Spain
NOT_YET_RECRUITINGUpper limb motor change
Evaluation with the ARAT scale
Time frame: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks
Cognitive function change
Cognitive evaluation with TAP (alertness, sustained and divided attention, selective attention/flexibility, spatial attention, and working memory).
Time frame: 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
Time frame: From enrollment to the end of treatment at 12 weeks, and follow-up at 20 weeks
Emotional change
Assessed with the Hamilton Depression Scale
Time frame: 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
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
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
Time frame: At the end of the study, at 20 weeks.
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