Intelligent bio robotic prosthetic arm system using HCI

Intelligent bio robotic prosthetic arm system using HCI | 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PDF Research Article Intelligent bio robotic prosthetic arm system using HCI Anuj singh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8575534/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 We need hand-eye coordination to do many things in our daily lives. If you lose the ability to take care of yourself, you will lose a lot. People often can't fully use prosthetic hands' capabilities because they are usually hard to use. As a result, prosthetic hands don't work as well as they could. This study seeks to investigate the development of an intelligent bionic robotic hand that can detect the object it is grasping and autonomously modify its grip strength. The goal is to fix the problems that current prosthetic technologies have. This method uses residual muscle impulses as built-in input to power the prosthetic's motor. It can accurately predict the path of the user's hand movement because it knows how the user's muscles work. This is possible because of new technologies in machine learning and vision. The system can better do tasks like manipulating and grasping by watching objects in real time. This method is easier to learn because it is similar to how people naturally use their hands. This study is important because it shows that machines can get tactile feedback. This gives users a stronger feeling of control and emotional connection. This technology is much better than older prosthetics because it can find targets with 68% to 87% accuracy. The goal of the research is to lower costs by using cheap parts like electromyography (EMG) sensors, Raspberry Pi, Arduino, and 3D-printed prosthetic parts. The main goal of this research is to make prosthetics better, so they are easier to use and can be used by more people. This will make a big difference in the lives of people who need prosthetics. Machine Learning Python OpenCV Real-time Object Detection Electromyography (EMG) Raspberry Pi Arduino Motor Control 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-8575534","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":572978325,"identity":"bd7b0ccb-3c62-4821-aa04-0f1798f323d5","order_by":0,"name":"Anuj 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HCI","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":"Machine Learning, Python, OpenCV, Real-time Object Detection, Electromyography (EMG), Raspberry Pi, Arduino, Motor Control","lastPublishedDoi":"10.21203/rs.3.rs-8575534/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8575534/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe need hand-eye coordination to do many things in our daily lives. If you lose the ability to take care of yourself, you will lose a lot. People often can't fully use prosthetic hands' capabilities because they are usually hard to use. As a result, prosthetic hands don't work as well as they could. This study seeks to investigate the development of an intelligent bionic robotic hand that can detect the object it is grasping and autonomously modify its grip strength. The goal is to fix the problems that current prosthetic technologies have. This method uses residual muscle impulses as built-in input to power the prosthetic's motor. It can accurately predict the path of the user's hand movement because it knows how the user's muscles work. This is possible because of new technologies in machine learning and vision. The system can better do tasks like manipulating and grasping by watching objects in real time. This method is easier to learn because it is similar to how people naturally use their hands. This study is important because it shows that machines can get tactile feedback. This gives users a stronger feeling of control and emotional connection. This technology is much better than older prosthetics because it can find targets with 68% to 87% accuracy. The goal of the research is to lower costs by using cheap parts like electromyography (EMG) sensors, Raspberry Pi, Arduino, and 3D-printed prosthetic parts. The main goal of this research is to make prosthetics better, so they are easier to use and can be used by more people. This will make a big difference in the lives of people who need prosthetics.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e","manuscriptTitle":"Intelligent bio robotic prosthetic arm system using HCI","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-13 12:36:51","doi":"10.21203/rs.3.rs-8575534/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"8e3e217d-2725-4d6b-bd63-ff72a11a32b5","owner":[],"postedDate":"January 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-20T12:31:48+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-13 12:36:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8575534","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8575534","identity":"rs-8575534","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}