A suitable EEG System for Cognitive Monitoring in Aphasia Rehabilitation: A Pilot Feasibility Study

A suitable EEG System for Cognitive Monitoring in Aphasia Rehabilitation: A Pilot Feasibility Study | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 4 March 2026 V1 Latest version Share on A suitable EEG System for Cognitive Monitoring in Aphasia Rehabilitation: A Pilot Feasibility Study Authors : Fernando Concatto 0000-0003-4361-7134 , Maurício Pasetto de Freitas , Evelio González-Dalmau [email protected] , Eduardo Legal , and Alejandro García Ramírez 0000-0002-1816-0016 Authors Info & Affiliations https://doi.org/10.22541/au.177260770.08096523/v1 139 views 60 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Traditional assessment instruments for post-stroke aphasia are typically extensive and asynchronous, providing results only after full administration. This delay limits their suitability for continuous clinical monitoring and real-time adaptive therapeutic adjustments. Objective: This study evaluates the feasibility of a low-cost, low-density EEG-based framework designed for the continuous estimation of working memory capacity as a key functional biomarker of rehabilitation progress. Methods: Electroencephalography (EEG) data were acquired from aphasic and control participants using a portable OpenBCI platform and a customized 3D-printed helmet of an n-back paradigm. Event-related potential (ERP) features, including P100, N100, P200, N200, and P300, were extracted to train linear (OLS) and a non-linear Support Vector Regression (SVR) model with a radial basis function (RBF) kernel against a composite ground-truth index (W). Results: Non-linear SVR models demonstrated superior performance and scalability compared to linear approaches. For groupings of 32 epochs, a statistically significant improvement was identified (p=0.04), with non-linear models showing a reduction in RMSE up to six times greater than linear models as effective training samples increased. Conclusion: These findings provide a proof-of-concept for a deployable, technology-assisted system capable of supporting individualized and adaptive cognitive monitoring in clinical post-stroke rehabilitation settings. Supplementary Material File (iet_healthcare_technology_letters.pdf) Download 782.38 KB File (main.tex) Download 31.78 KB Information & Authors Information Version history V1 Version 1 04 March 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords biomedical electronics brain-computer interfaces data acquisition portable instruments signal classification Authors Affiliations Fernando Concatto 0000-0003-4361-7134 Universidade do Vale do Itajai View all articles by this author Maurício Pasetto de Freitas Universidade do Vale do Itajai View all articles by this author Evelio González-Dalmau [email protected] Cuban Neuroscience Center View all articles by this author Eduardo Legal UNIVALI View all articles by this author Alejandro García Ramírez 0000-0002-1816-0016 UNIVALI View all articles by this author Metrics & Citations Metrics Article Usage 139 views 60 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Fernando Concatto, Maurício Pasetto de Freitas, Evelio González-Dalmau, et al. A suitable EEG System for Cognitive Monitoring in Aphasia Rehabilitation: A Pilot Feasibility Study. Authorea . 04 March 2026. 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