Translational Evaluation of a Machine Learning-Based Interactive Lab for Aphasia Rehabilitation in Post Stroke Patients

Abstract

The proposed interactive lab integrates gamified therapy with real time, explainable machine learning assessment, demonstrates clinical efficacy in improving language outcomes, and offers a scalable framework for AI-driven, adaptive neurorehabilitation that has been clinically validated within a hospital setting and designed to align with Taiwan Food and Drug Administration (TFDA) software-as-a-medical-device (SaMD) regulatory principles for translational deployment in clinical environments and hospital investigational use guidelines. Clinical Impact-The integration of gamified digital therapy with machine learning analytics supports personalized, data driven intervention for aphasia rehabilitation in both clinical and home settings, particularly in resource limited environments. Clinical and Translational Impact Statement-This study supports Clinical Research by demonstrating that AI-powered digital therapy significantly improves language outcomes in post-stroke aphasia patients and offers a pathway to scalable, at home neurorehabilitation.

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