MI-BMPI Motor Imagery Brain--Mobile Phone Dataset and Performance Evaluation of Voting Ensembles Utilizing QPDM

MI-BMPI Motor Imagery Brain--Mobile Phone Dataset and Performance Evaluation of Voting Ensembles Utilizing QPDM | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article MI-BMPI Motor Imagery Brain--Mobile Phone Dataset and Performance Evaluation of Voting Ensembles Utilizing QPDM Cagatay Murat Yilmaz, Bahar Hatipoglu Yilmaz, Cemal Kose This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4268007/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract EEG-based interfaces are an active area of research that has great potential. We therefore focused on classifying motor imaging (MI) tasks from various problem areas. Because of that, we applied MI patterns to voting ensembles differently and constructed voters. They employ quasi-probabilistic distribution models based sub-classifiers made up of different frequency bands and time segments. Much previous work focused on just a few MI tasks for BCIs. To that end, we constructed a new mobile EEG dataset, abbreviated as MI-BMPI, containing two major gestures for mobile phone interfaces, and thus brain-mobile phone interfaces (BMPI) was added to the problem domain. In the research experiments, a consumer market EEG system, the mobile wireless Emotiv EPOC Flex neuroheadset, was used. Experiments were carried out on the BCI Competition IV Dataset 2a and MI-BMPI. On the BCI and BMPI datasets, promising results were obtained in classifying various MI tasks. In conclusion, new solutions were introduced for tougher EEG-based interfaces, which have potential in the classification of MI tasks and the development of EEG-based interfaces. In addition to the average performance improvements, more stable results were achieved for both subject and task variations. Computational Neuroscience Artificial Intelligence and Machine Learning Electroencephalography Motor imagery Brain-mobile phone interface Brain-computer interface Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4268007","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":291238765,"identity":"67c9125e-8e24-477b-90d7-27ba36459e04","order_by":0,"name":"Cagatay Murat Yilmaz","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYJCCAw+ABD8PmM1MpJYEICHZwwzVwkaMHpAWgzPEauGfdsbwQGKOnb3xmfPHJBgqrBMb5Hsf4NUicTvH4EDitmRms7PNbBIMZ9ITG9jYDfBqMZAGa2FmMzvPzCbB2HYYqIWAy6Ba6nmM+0Fa/hGv5bCEAS/QYYwNRGiRuJ1WANRy3EDizGFji4Rj6cZtbGn4tfDPTt784eO2anv+nsSHNz7UWMv2Mx/Dr4WBgQMpfBIYiIpJ9geE1YyCUTAKRsHIBgAe8z+a0N5zoAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-6513-7337","institution":"Karadeniz Technical University","correspondingAuthor":true,"prefix":"","firstName":"Cagatay","middleName":"Murat","lastName":"Yilmaz","suffix":""},{"id":291238766,"identity":"3333be78-4f64-4819-8983-d6eeab607f5f","order_by":1,"name":"Bahar Hatipoglu Yilmaz","email":"","orcid":"","institution":"Karadeniz Technical University","correspondingAuthor":false,"prefix":"","firstName":"Bahar","middleName":"Hatipoglu","lastName":"Yilmaz","suffix":""},{"id":291238767,"identity":"54fc21a0-baf3-46bb-a231-1e376adba8a4","order_by":2,"name":"Cemal Kose","email":"","orcid":"","institution":"Karadeniz Technical University","correspondingAuthor":false,"prefix":"","firstName":"Cemal","middleName":"","lastName":"Kose","suffix":""}],"badges":[],"createdAt":"2024-04-15 07:38:34","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4268007/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4268007/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54747638,"identity":"5a8efe32-bef4-4210-b10b-76115005462c","added_by":"auto","created_at":"2024-04-16 07:42:47","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5431761,"visible":true,"origin":"","legend":"","description":"","filename":"snarticleKopya.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4268007/v1_covered_dac18893-d01c-4a6d-bb5b-83092a27c35b.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eMI-BMPI Motor Imagery Brain--Mobile Phone Dataset and Performance Evaluation of Voting Ensembles Utilizing QPDM\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Electroencephalography, Motor imagery, Brain-mobile phone interface, Brain-computer interface","lastPublishedDoi":"10.21203/rs.3.rs-4268007/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4268007/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEEG-based interfaces are an active area of research that has great potential. 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