Non-Invasive EEG-Based Brain-Computer Interface for Real-Time Prosthetic Hand Control

Non-Invasive EEG-Based Brain-Computer Interface for Real-Time Prosthetic Hand Control | 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 Non-Invasive EEG-Based Brain-Computer Interface for Real-Time Prosthetic Hand Control Maryam Iqbal, Momna Majeed, Zainab Batool, Amna Batool, Luqman Khan, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8671988/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 This paper highlights a non-invasive EEG-controlled brain–computer interface BCI system for real-time control over a developed prosthetic hand system. Motor imagery trials involving opening, closing, grasping, and resting states were conducted using a single-channel NeuroSky MindWave helmet to produce EEG signals. These EEGs were processed in real-time to extract features and employ machine learning to decode intentions and control outputs. This system proved quite effective in terms of classification accuracy and precision, at approximately 87% and 88%, respectively, with a very short latency to enable smooth control over the prosthetic hand system. By comparing this system to conventional EMG technology or using invasive electrode technology, this technology prioritizes ease of use and a sense of safety and usability in patients. This system proved very effective in controlling the prosthetic hand to perform intended tasks, thereby suggesting a potential improvement in practical usability and feasibility in terms of quality-of-life enhancement in patients with lost upper limbs. Electroencephalography (EEG) Electromyography (EMG) Prosthetic Control Neuro-prosthetic Full Text Additional Declarations No competing interests reported. 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8671988","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":590388126,"identity":"46d85493-cd9a-4043-85ea-ecd2df007ba5","order_by":0,"name":"Maryam Iqbal","email":"data:image/png;base64,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","orcid":"","institution":"Bahria University","correspondingAuthor":true,"prefix":"","firstName":"Maryam","middleName":"","lastName":"Iqbal","suffix":""},{"id":590388127,"identity":"6ce42b30-8af0-4ed1-92cb-dcf82264e178","order_by":1,"name":"Momna Majeed","email":"","orcid":"","institution":"Bahria University","correspondingAuthor":false,"prefix":"","firstName":"Momna","middleName":"","lastName":"Majeed","suffix":""},{"id":590388128,"identity":"6981c7d7-d825-472e-8378-d4f0003788e9","order_by":2,"name":"Zainab Batool","email":"","orcid":"","institution":"Bahria University","correspondingAuthor":false,"prefix":"","firstName":"Zainab","middleName":"","lastName":"Batool","suffix":""},{"id":590388129,"identity":"75803557-beee-4fd5-8adc-f30415731b60","order_by":3,"name":"Amna Batool","email":"","orcid":"","institution":"Bahria University","correspondingAuthor":false,"prefix":"","firstName":"Amna","middleName":"","lastName":"Batool","suffix":""},{"id":590388130,"identity":"64b9098f-2a07-41d6-9958-2ed7b7a9d578","order_by":4,"name":"Luqman Khan","email":"","orcid":"","institution":"Bahria University","correspondingAuthor":false,"prefix":"","firstName":"Luqman","middleName":"","lastName":"Khan","suffix":""},{"id":590388131,"identity":"c35a6ad6-71d2-4b1c-a97e-6e74698d69f6","order_by":5,"name":"Huzaifa Malik","email":"","orcid":"","institution":"Bahria University","correspondingAuthor":false,"prefix":"","firstName":"Huzaifa","middleName":"","lastName":"Malik","suffix":""}],"badges":[],"createdAt":"2026-01-22 16:40:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8671988/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8671988/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104887636,"identity":"115460fd-5281-4cb7-8037-7ab0bc872cb8","added_by":"auto","created_at":"2026-03-18 10:12:28","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":792128,"visible":true,"origin":"","legend":"","description":"","filename":"BCIHandProstheticdeviceIJRAFinal.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8671988/v1_covered_23e24e89-4683-4d63-9d1b-d08dd5beccdb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Non-Invasive EEG-Based Brain-Computer Interface for Real-Time Prosthetic Hand Control","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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 (EEG), Electromyography (EMG), Prosthetic Control, Neuro-prosthetic","lastPublishedDoi":"10.21203/rs.3.rs-8671988/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8671988/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This paper highlights a non-invasive EEG-controlled brain–computer interface BCI system for real-time control over a developed prosthetic hand system. 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