Quantum Leap in Cardiac Prognosis: EMIP-CardioPPG’s Pioneering Approach to Early Myocardial Infarction Prediction

Quantum Leap in Cardiac Prognosis: EMIP-CardioPPG’s Pioneering Approach to Early Myocardial Infarction Prediction | 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 Quantum Leap in Cardiac Prognosis: EMIP-CardioPPG’s Pioneering Approach to Early Myocardial Infarction Prediction Abhishek Shrivastava, Santosh Kumar, N. Srinivas Naik This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4585971/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Sep, 2024 Read the published version in Signal, Image and Video Processing → Version 1 posted 10 You are reading this latest preprint version Abstract Cardiovascular disease (CVD) encompasses conditions affecting the heart and blood vessels, leading to ailments such as coronary artery disease, heart failure, and myocardial infarction (MI), commonly referred to as a heart attack, which occurs when blood flow to the heart is obstructed. Early prediction of MI is vital to prevent severe damage and enhance survival rates. Traditionally, an electrocardiogram (ECG) is employed to detect cardiovascular anomalies, but its requirement for multiple electrodes placed on various body locations makes continuous monitoring difficult. Current research gaps involve the necessity for medical assistance during ECG monitoring, data variability, early symptom prediction, and limited data availability due to the sensitive nature of medical records. To address these issues, we introduce EMIP-CardioPPG, a novel mathematical framework for early MI prediction using CardioPPG, a non-invasive method that utilizes photoplethysmography (PPG) signals to monitor heart rate (HR) and detect cardiovascular abnormalities. Our approach comprises four steps: first, acquiring data from the same individual using two different sources, a self-created IoMT device and a 4-channel BIOAC-MP 36 device; second, preprocessing the data by denoising, filtering, normalizing, and removing motion arti-facts; and third, employing mathematical calculations to determine heart rate variability (HRV) and HR, enhancing PPG signal features for early MI prediction. fourth, Evaluate our model performance using machine learning (ML) algorithms such as ridge regression (RR), support vector classifier (SVC), independent component analysis (ICA), singular value decomposition (SVD), random forest (RF), and XGBoost, achieving high accuracy of 97.91% for HRV from our IomT device and 98.83% for HR from our BOPAC-MP 36. In future studies, we will compare our results with state-of-the-art algorithms and evaluate our model’s performance using cardiac images. Myocardial Infarction Heart Rate Variability Electrocardiogram Photoplethysmogram Internet of Medical Things Machine Learning Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 04 Sep, 2024 Read the published version in Signal, Image and Video Processing → Version 1 posted Editorial decision: Revision requested 16 Jul, 2024 Reviews received at journal 15 Jul, 2024 Reviewers agreed at journal 22 Jun, 2024 Reviews received at journal 18 Jun, 2024 Reviewers agreed at journal 17 Jun, 2024 Reviewers agreed at journal 17 Jun, 2024 Reviewers invited by journal 17 Jun, 2024 Editor assigned by journal 15 Jun, 2024 Submission checks completed at journal 15 Jun, 2024 First submitted to journal 15 Jun, 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-4585971","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":320018458,"identity":"6328c812-0571-4d30-8a02-80bceba32c85","order_by":0,"name":"Abhishek Shrivastava","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYDACCR6GA4wNDAYM7I0NBxIgYgZgRFgLz0GglgQitTCAtUiAlMO14AH8s3sPHvy5w8ZYfubjxgMPf9zJZ2Bv3ibBUHAHtyV3ziUc5j2TZmZwOxHksGeWDTzHyiQYDJ7htuZGjsFhxrbDNgbSYC2HgS7MMQNqOYxThzxQy8Gfbf9t5GcehGqRf4NfiwFQywHetgNmDDcYYbbw4NdieOeMwWHetmRjgzMgh6UdNmDjSSu2SMCjRe52j/HHn212hvPbjz/++MPmsAE/++GNNz78wa0FE7CBiAQSNIyCUTAKRsEowAQAaTBc0fF101kAAAAASUVORK5CYII=","orcid":"","institution":"CSE, IIIT Naya Raipur","correspondingAuthor":true,"prefix":"","firstName":"Abhishek","middleName":"","lastName":"Shrivastava","suffix":""},{"id":320018459,"identity":"32249226-72a0-43cc-9cf3-3d766367777b","order_by":1,"name":"Santosh Kumar","email":"","orcid":"","institution":"CSE, IIIT Naya Raipur","correspondingAuthor":false,"prefix":"","firstName":"Santosh","middleName":"","lastName":"Kumar","suffix":""},{"id":320018460,"identity":"ce97a438-a84f-49aa-b43e-f055c11232a8","order_by":2,"name":"N. 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