{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T19:54:09Z","timestamp":1776887649254,"version":"3.51.2"},"reference-count":40,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2024,9,22]],"date-time":"2024-09-22T00:00:00Z","timestamp":1726963200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Interreg V-A Italia-Slovenia 2014\u20132020 Programme","award":["1473079734"],"award-info":[{"award-number":["1473079734"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Brain\u2013computer interfaces (BCIs) are promising tools for motor neurorehabilitation. Achieving a balance between classification accuracy and system responsiveness is crucial for real-time applications. This study aimed to assess how the duration of time windows affects performance, specifically classification accuracy and the false positive rate, to optimize the temporal parameters of MI-BCI systems. We investigated the impact of time window duration on classification accuracy and false positive rate, employing Linear Discriminant Analysis (LDA), Multilayer Perceptron (MLP), and Support Vector Machine (SVM) on data acquired from six post-stroke patients and on the external BCI IVa dataset. EEG signals were recorded and processed using the Common Spatial Patterns (CSP) algorithm for feature extraction. Our results indicate that longer time windows generally enhance classification accuracy and reduce false positives across all classifiers, with LDA performing the best. However, to maintain the real-time responsiveness, crucial for practical applications, a balance must be struck. The results suggest an optimal time window of 1\u20132 s, offering a trade-off between classification performance and excessive delay to guarantee the system responsiveness. These findings underscore the importance of temporal optimization in MI-BCI systems to improve usability in real rehabilitation scenarios.<\/jats:p>","DOI":"10.3390\/s24186125","type":"journal-article","created":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T08:56:06Z","timestamp":1727168166000},"page":"6125","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Optimizing Real-Time MI-BCI Performance in Post-Stroke Patients: Impact of Time Window Duration on Classification Accuracy and Responsiveness"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6156-1464","authenticated-orcid":false,"given":"Aleksandar","family":"Miladinovi\u0107","sequence":"first","affiliation":[{"name":"Institute for Maternal and Child Health-IRCCS \u201cBurlo Garofolo\u201d, 34137 Trieste, Italy"}]},{"given":"Agostino","family":"Accardo","sequence":"additional","affiliation":[{"name":"Department of Engineering and Architecture, University of Trieste, 34127 Trieste, Italy"}]},{"given":"Joanna","family":"Jarmolowska","sequence":"additional","affiliation":[{"name":"Science and Research Centre Koper, Institute for Kinesiology Research, 6000 Koper, Slovenia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7420-2137","authenticated-orcid":false,"given":"Uros","family":"Marusic","sequence":"additional","affiliation":[{"name":"Science and Research Centre Koper, Institute for Kinesiology Research, 6000 Koper, Slovenia"},{"name":"Department of Health Sciences, Alma Mater Europaea University, 2000 Maribor, Slovenia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8307-4360","authenticated-orcid":false,"given":"Milo\u0161","family":"Aj\u010devi\u0107","sequence":"additional","affiliation":[{"name":"Department of Engineering and Architecture, University of Trieste, 34127 Trieste, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1016\/j.tins.2006.07.004","article-title":"Brain-Machine Interfaces: Past, Present and Future","volume":"29","author":"Lebedev","year":"2006","journal-title":"Trends Neurosci."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Wierzga\u0142a, P., Zapa\u0142a, D., Wojcik, G.M., and Masiak, J. 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