https://m2.mtmt.hu/ hun 2026-09-21 03:10 JournalArticle 34771485 VALIDATED true Funding Agency and Grant Number: Coleman Fung Foundation Funding text: The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was partially funded by the Charley Sinclair Foundation and the Coleman Fung Foundation. 0 false 2026-07-14T12:50:44.534+0000 2026-04-09T10:41:32.555+0000 2024-04-05T07:19:22.502+0000 true 10093553 Fi Tamás /api/admin/10093553 Admin true 2026-05-18T02:46:34.826+0000 2025-06-19T13:12:36.904+0000 true 10062062 Gere Tamásné /api/admin/10062062 Admin true 10062062 true false true 24 24 /api/publicationtype/24 PublicationType 1 true 24 JournalArticle true 10000059 Article true 24 24 /api/publicationtype/24 PublicationType 1 true 24 JournalArticle /api/subtype/10000059 Szakcikk SubType 101 true 10000059 true 1 /api/category/1 Category true 1 Rácz, F.S. Combining detrended cross-correlation analysis with Riemannian geometry-based classification for improved brain-computer interface performance true true /api/journal/39990 REVIEWED true false 39990 false 39990 true 1662-4548 1662-453X Journal FOREIGN 18 1271831 1271831 17 2024 Riemannian geometry-based classification (RGBC) gained popularity in the field of brain-computer interfaces (BCIs) lately, due to its ability to deal with non-stationarities arising in electroencephalography (EEG) data. Domain adaptation, however, is most often performed on sample covariance matrices (SCMs) obtained from EEG data, and thus might not fully account for components affecting covariance estimation itself, such as regional trends. Detrended cross-correlation analysis (DCCA) can be utilized to estimate the covariance structure of such signals, yet it is computationally expensive in its original form. A recently proposed online implementation of DCCA, however, allows for its fast computation and thus makes it possible to employ DCCA in real-time applications. In this study we propose to replace the SCM with the DCCA matrix as input to RGBC and assess its effect on offline and online BCI performance. First we evaluated the proposed decoding pipeline offline on previously recorded EEG data from 18 individuals performing left and right hand motor imagery (MI), and benchmarked it against vanilla RGBC and popular MI-detection approaches. Subsequently, we recruited eight participants (with previous BCI experience) who operated an MI-based BCI (MI-BCI) online using the DCCA-enhanced Riemannian decoder. Finally, we tested the proposed method on a public, multi-class MI-BCI dataset. During offline evaluations the DCCA-based decoder consistently and significantly outperformed the other approaches. Online evaluation confirmed that the DCCA matrix could be computed in real-time even for 22-channel EEG, as well as subjects could control the MI-BCI with high command delivery (normalized Cohen's κ: 0.7409 ± 0.1515) and sample-wise MI detection (normalized Cohen's κ: 0.5200 ± 0.1610). Post-hoc analysis indicated characteristic connectivity patterns under both MI conditions, with stronger connectivity in the hemisphere contralateral to the MI task. Additionally, fractal scaling exponent of neural activity was found increased in the contralateral compared to the ipsilateral motor cortices (C4 and C3 for left and right MI, respectively) in both classes. Combining DCCA with Riemannian geometry-based decoding yields a robust and effective decoder, that not only improves upon the SCM-based approach but can also provide relevant information on the neurophysiological processes behind MI. 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false false false false 2024-04-04T07:27:43.078+0000 Népegészségtani Intézet (SE / AOK / I); Transzlációs Medicina Intézet (SE / AOK / I); Élettani Intézet (SE / AOK / I) 4 12 3 9 0 true Language 10002 /api/language/10002 Angol English true 2 true PersonAuthorship 116033596 /api/authorship/116033596 1 0.111 true false true Author 10059431 /api/author/10059431 Rácz Frigyes Sámuel true 10059431 true Rácz F.S. true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 116033597 /api/authorship/116033597 2 0.11111111 false false false Kumar S. true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 116033598 /api/authorship/116033598 3 0.111 false false false Author 10081142 /api/author/10081142 Káposzta Zalán true true Káposzta Z. true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 116033599 /api/authorship/116033599 4 0.11111111 false false false Alawieh H. true 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target="_blank">Rácz F.S. ✉ (<span class="authorship-author-name">Rácz Frigyes Sámuel</span> <span class="authorAux-mtmt"> Élettan</span>) </a> </span> <span class="author-affil"><span title="Semmelweis Egyetem">SE</span>/<span title="Általános Orvostudományi Kar">AOK</span>/<span title="Intézet">I</span>/Élettani Intézet</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Kumar S. </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10081142"><a href="/gui2/?type=authors&mode=browse&sel=10081142" target="_blank">Káposzta Z. (<span class="authorship-author-name">Káposzta Zalán</span> <span class="authorAux-mtmt"> Fraktálélettan és Hálózatelméleti Analízis</span>) </a> </span> <span class="author-affil"><span title="Semmelweis Egyetem">SE</span>/<span title="Általános Orvostudományi Kar">AOK</span>/<span title="Intézet">I</span>/Élettani Intézet</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Alawieh H. </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Liu D.H. </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Liu R. </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10081139"><a href="/gui2/?type=authors&mode=browse&sel=10081139" target="_blank">Czoch Á. (<span class="authorship-author-name">Czoch Ákos</span> <span class="authorAux-mtmt"> Élettan</span>) </a> </span> <span class="author-affil"><span title="Semmelweis Egyetem">SE</span>/<span title="Általános Orvostudományi Kar">AOK</span>/<span title="Intézet">I</span>/Élettani Intézet</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10032249"><a href="/gui2/?type=authors&mode=browse&sel=10032249" target="_blank">Mukli P. (<span class="authorship-author-name">Mukli Péter</span> <span class="authorAux-mtmt"> Élettan, megelőző orvostan és népegészségtan</span>) </a> </span> <span class="author-affil"><span title="Semmelweis Egyetem">SE</span>/<span title="Általános Orvostudományi Kar">AOK</span>/<span title="Intézet">I</span>/Élettani Intézet; <span title="Semmelweis Egyetem">SE</span>/<span title="Általános Orvostudományi Kar">AOK</span>/<span title="Intézet">I</span>/Népegészségtani Intézet; <span title="Semmelweis Egyetem">SE</span>/<span title="Általános Orvostudományi Kar">AOK</span>/<span title="Intézet">I</span>/Transzlációs Medicina Intézet</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Millán J.D.R. </span> </div> </div> <div class="title"><a href="/gui2/?mode=browse&params=publication;34771485" target="_blank">Combining detrended cross-correlation analysis with Riemannian geometry-based classification for improved brain-computer interface performance</a></div> <div> <span class="journal-title">FRONTIERS IN NEUROSCIENCE</span> <span class="journal-issn">(<a target="_blank" href="https://portal.issn.org/resource/ISSN/1662-4548">1662-4548</a> <a target="_blank" href="https://portal.issn.org/resource/ISSN/1662-453X">1662-453X</a>)</span>: <span class="journal-volume">18</span> <span class="page"> Paper 1271831. 17 p. </span> <span class="year">(2024)</span> </div> <div class="pub-footer"> <span class="language" xmlns="http://www.w3.org/1999/html">Nyelv: Angol | </span> <span class="identifiers"> <span class="id identifier oa_GOLD" title=" Gold "> <a style="color:blue" title="10.3389/fnins.2024.1271831" target="_blank" href="https://doi.org/10.3389/fnins.2024.1271831"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="001191942600001" target="_blank" href="https://www.webofscience.com/wos/woscc/full-record/001191942600001"> WoS </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="85188913472" target="_blank" href="http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85188913472"> Scopus </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="38550567" target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=38550567&dopt=Abstract"> PubMed </a> </span> <span class="id identifier oa_NONE" title=" Nincs "> <a style="color:blue" title="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188913472&doi=10.3389%2Ffnins.2024.1271831&partnerID=40&md5=33eee5cf49d07bbc90ae82ade0cad148" target="_blank" href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188913472&doi=10.3389%2Ffnins.2024.1271831&partnerID=40&md5=33eee5cf49d07bbc90ae82ade0cad148"> Egyéb URL </a> </span> </span> <OnlyViewableByAuthor><div class="ratings"> <div class="journal-subject">Folyóirat szakterülete: Scopus - Neuroscience (miscellaneous)&nbsp;&nbsp;&nbsp;SJR indikátor:&nbsp;Q2</div> </div></OnlyViewableByAuthor> <div class="publication-citation" style="margin-left: 0.5cm;"> <span title="Nyilvános idézőközlemények összesen, említések nélkül" class="citingPub-count">Nyilvános idéző összesen: 10</span> | Független: 7 | Függő: 3 | Nem jelölt: 0 | WoS jelölt: 8 | Scopus jelölt:&nbsp;10 | WoS/Scopus jelölt:&nbsp;10 | DOI jelölt:&nbsp;10 </div> <div class="publication-citation"> <a target="_blank" href="/api/publication?cond=citations.related;eq;34771485&sort=publishedYear,desc&sort=title"> Idézett közlemények száma: 9 </a> </div> <div class="mtid"><span class="long-pub-mtid">Közlemény: 34771485</span> | <span class="status-data status-VALIDATED"> Egyeztetett </span> Forrás Idéző | <span class="type-subtype">Folyóiratcikk ( Szakcikk ) </span> | <span class="pub-category">Tudományos</span> | <span class="publication-sourceOfData">Scopus</span> </div> <div class="lastModified">Utolsó módosítás: 2026.04.09. 12:41 Sonnevend Kinga (SE_AOK_Élettan_Admin5_SK, admin) </div> <pre class="comment" style="margin-top: 0; margin-bottom: 0;"><u>Megjegyzés</u>: Funding Agency and Grant Number: Coleman Fung Foundation Funding text: The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was partially funded by the Charley Sinclair Foundation and the Coleman Fung Foundation.</pre> </div></div>