How fast is ECG signal? Propagation of the endogenous electromagnetic wave of cardiac origin

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Abstract

A satisfactory model of the biopotentials, propagating through the human body, is essential for medical diagnostics, particularly for cardiovascular diseases. In our study, we develop the theory, that the propagation of biopotential of cardiac origin (ECG signal) may be treated as the propagation of low-frequency endogenous electromagnetic (EM) wave through the human body. We show that within this approach, the velocity of the ECG signal can be theoretically estimated, like for any other wave and physical medium, from the refraction index of the tissue in an appropriate frequency range. We confirm the theoretical predictions by the results of a direct measurement of the ECG signal propagation velocity and obtain mean velocity as low as v=1500 m/s. The results shed new light on our understanding of biopotential propagation through living tissue. This finding may improve medical diagnostics based on the impedance spectroscopy and electrocardiographic imaging, not to mention ECG, EEG and virtually all electric measurements. Better understanding of the underlying phenomena may also lead to new therapy solutions in various clinical contexts.
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How fast is ECG signal? Propagation of the endogenous electromagnetic wave of cardiac origin | 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 Article How fast is ECG signal? Propagation of the endogenous electromagnetic wave of cardiac origin Teodor Buchner, Maryla Zajdel, Kazimierz Pęczalski, Paweł Nowak This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1916139/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Mar, 2023 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract A satisfactory model of the biopotentials, propagating through the human body, is essential for medical diagnostics, particularly for cardiovascular diseases. In our study, we develop the theory, that the propagation of biopotential of cardiac origin (ECG signal) may be treated as the propagation of low-frequency endogenous electromagnetic (EM) wave through the human body. We show that within this approach, the velocity of the ECG signal can be theoretically estimated, like for any other wave and physical medium, from the refraction index of the tissue in an appropriate frequency range. We confirm the theoretical predictions by the results of a direct measurement of the ECG signal propagation velocity and obtain mean velocity as low as v=1500 m/s. The results shed new light on our understanding of biopotential propagation through living tissue. This finding may improve medical diagnostics based on the impedance spectroscopy and electrocardiographic imaging, not to mention ECG, EEG and virtually all electric measurements. Better understanding of the underlying phenomena may also lead to new therapy solutions in various clinical contexts. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 22 Mar, 2023 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Major revision 09 Jan, 2023 Reviews received at journal 08 Jan, 2023 Reviewers agreed at journal 28 Nov, 2022 Reviews received at journal 22 Sep, 2022 Reviewers agreed at journal 22 Sep, 2022 Reviewers invited by journal 22 Sep, 2022 Editor assigned by journal 22 Sep, 2022 Editor invited by journal 22 Sep, 2022 Submission checks completed at journal 22 Sep, 2022 First submitted to journal 01 Aug, 2022 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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