Detecting Human Activities In COMA Patients Using ML Algorithm

Detecting Human Activities In COMA Patients Using ML Algorithm | 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 Detecting Human Activities In COMA Patients Using ML Algorithm Aditi Singh, Utkarsh Singh, Vivek Pandey, Nilesh Deotale, Poorva Talekar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4969538/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Health monitoring systems employing machine learning facilitate the collection and collaboration of data from comatose patients, leveraging sensors in hospitals via IoT technology. This data aids doctors in enhancing and managing the health of comatose patients during emergency situations. The hardware platform for this project integrates sensors and cameras capable of internet communication, enabling remote access for doctors via smartphones. This innovative approach empowers doctors to access and monitor patients' health statuses globally. Sensors gather vital medical data including heart rate, blood pressure, and other relevant parameters, which is then transmitted to a medical server via the internet. A series of cameras further monitor the patient, with data being securely stored for access by doctors and patient relatives through a dedicated application. In the event of sensor values exceeding predefined thresholds, urgent alarms are triggered, alerting both patients and medical staff. Continuous monitoring of patient health parameters ensures prompt intervention when necessary. Routine monitoring data sent to doctors via servers aids in diagnostics, facilitating precise treatment strategies. By harnessing IoT for data collection, patients benefit from enhanced medical care at reduced costs, promoting easier recovery. The project boasts an impressive execution rate of 99.7%, indicative of its efficacy and reliability in real-world applications. Healthcare monitoring Motion analysis Patient care Coma Patient Activity Detection Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 29 Aug, 2024 Submission checks completed at journal 29 Aug, 2024 First submitted to journal 24 Aug, 2024 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. 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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-4969538","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":350308926,"identity":"9b8b3b1b-6d29-4695-bd8b-dacdcfc08b32","order_by":0,"name":"Aditi Singh","email":"","orcid":"","institution":"University of Mumbai","correspondingAuthor":false,"prefix":"","firstName":"Aditi","middleName":"","lastName":"Singh","suffix":""},{"id":350308927,"identity":"dba19464-e1dd-4cb4-bd74-2576248f4b8e","order_by":1,"name":"Utkarsh Singh","email":"","orcid":"","institution":"University of Mumbai","correspondingAuthor":false,"prefix":"","firstName":"Utkarsh","middleName":"","lastName":"Singh","suffix":""},{"id":350308928,"identity":"2024adf9-468e-4e34-aab9-aafc16079305","order_by":2,"name":"Vivek Pandey","email":"","orcid":"","institution":"University of Mumbai","correspondingAuthor":false,"prefix":"","firstName":"Vivek","middleName":"","lastName":"Pandey","suffix":""},{"id":350308929,"identity":"e845d95c-0c14-47f6-b265-b7c2d901366f","order_by":3,"name":"Nilesh Deotale","email":"","orcid":"","institution":"University of Mumbai","correspondingAuthor":false,"prefix":"","firstName":"Nilesh","middleName":"","lastName":"Deotale","suffix":""},{"id":350308930,"identity":"1f660e05-83c7-4b44-a011-d2d13748e911","order_by":4,"name":"Poorva Talekar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYFAC5gbGBjjHwAZIMDYewKeBh4ERWUtFGkhLAylazhwGU3i12LMfbHw4o+ZeHj977zOJn23n7da2HwbaUmMTjdMWnsRmww3Hiosle46bSfa23U7ediYRqOVYWm4DLi0MiW2SD9gSEjfcSGM24AVqMTsA1MLYcBi3Fv6H7T8f/INoMfzbdi7Z7PxDAlokEtsYN7aBtTA+5jlzwM7sBiFbbjxslpzZlwD0yzHGxzIVyQlmN4C2JODxC3t/8sGPPd8SgCHWxnDwjYGdvdn59IcPPtTY4NQCAwkwRmIDCpcYLfZEKB4Fo2AUjIIRBgBGemgrNLRduAAAAABJRU5ErkJggg==","orcid":"","institution":"University of Mumbai","correspondingAuthor":true,"prefix":"","firstName":"Poorva","middleName":"","lastName":"Talekar","suffix":""}],"badges":[],"createdAt":"2024-08-24 14:14:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4969538/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4969538/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":65446534,"identity":"b1358b80-1ed5-4d5a-9f55-4e1be3d46f98","added_by":"auto","created_at":"2024-09-27 14:10:10","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":442837,"visible":true,"origin":"","legend":"","description":"","filename":"DetectingHumanActivityinComaPatient..pdf","url":"https://assets-eu.researchsquare.com/files/rs-4969538/v1_covered_506c8d68-0639-452b-b45b-ff12e6b7b99f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Detecting Human Activities In COMA Patients Using ML Algorithm","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"the-journal-of-supercomputing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [The Journal of Supercomputing](https://www.springer.com/journal/11227)","snPcode":"11227","submissionUrl":"https://submission.nature.com/new-submission/11227/3","title":"The Journal of Supercomputing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Healthcare monitoring, Motion analysis, Patient care, Coma Patient, Activity Detection","lastPublishedDoi":"10.21203/rs.3.rs-4969538/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4969538/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHealth monitoring systems employing machine learning facilitate the collection and collaboration of data from comatose patients, leveraging sensors in hospitals via IoT technology. 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