Computational Analysis of a High-density Electrode to Scale the Electric Field Geometry and Intensity for Neurostimulation

Computational Analysis of a High-density Electrode to Scale the Electric Field Geometry and Intensity for Neurostimulation | 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 Computational Analysis of a High-density Electrode to Scale the Electric Field Geometry and Intensity for Neurostimulation Kegan Mancabelli, Albert H. Titus, Filip Stefanovic This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8950885/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 High-density grid electrodes can be configured to spatially scale the neurostimulation fields and enable the control of depth, intensity, and stimulation vectoring. In this study we computationally analyze a high density cluster electrode (HDCE) technology to measure its scalability and its effects on human tissue. The models are developed in Ansys using the Maxwell 3D Design modeler. More than 24 HDCE electrode configurations were analyzed and compared to standard 8mm Ag/AgCl electrodes. It was found that the HDCE electrode configurations can be selected to emulate the electrical field properties to within 1% of a standard 8mm Ag/AgCl electrode. Moreover, increasing the number of active electrode contacts in the HDCE non-linearly increases tissue voltage and field intensity at various tissue depths. Specifically, it was found that the sensitivity of tissue voltage and field intensity decreases with the number of active HDCE electrode contacts. Similarly, the different spatial configurations of the HDCE can change the field shape by up to 54%, while the field intensity can be scaled by up to 186%. Similarly, the vector of the stimulation field (i.e., stimulation vector) through the tissues can be adjusted by shifting active electrode positions. When comparing these electrodes to standard 8mm Ag/AgCl electrodes the results suggest a transformative impact of these technologies to optimize neurostimulation applications. The work presented here is part of a larger project aiming to develop next-generation scalable neurostimulation system that improve rehabilitation outcomes, and provide new adaptive solutions for personalized healthcare. Biomedical Engineering neurostimulation high-density sensors HD-EMG scalable electrodes Full Text Additional Declarations The authors declare no competing interests. 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. 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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-8950885","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":595920536,"identity":"efde416e-3a3b-4e61-b510-089e44b50d16","order_by":0,"name":"Kegan Mancabelli","email":"","orcid":"","institution":"Cornell University","correspondingAuthor":false,"prefix":"","firstName":"Kegan","middleName":"","lastName":"Mancabelli","suffix":""},{"id":595920537,"identity":"3401af1c-67bb-4046-96e5-0d4610f390ce","order_by":1,"name":"Albert H. 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