{"id":15072,"date":"2025-12-08T14:08:00","date_gmt":"2025-12-08T12:08:00","guid":{"rendered":"https:\/\/dx-systems.com\/?p=15072"},"modified":"2026-06-11T14:38:11","modified_gmt":"2026-06-11T11:38:11","slug":"artifact-correction-method-for-m-response-usingunet1d-network","status":"publish","type":"post","link":"https:\/\/dx-systems.com\/en\/artifact-correction-method-for-m-response-usingunet1d-network\/","title":{"rendered":"Artifact Correction Method for M-response usingUNet1D Network"},"content":{"rendered":"\n

Kostiantyn Zabrodin
Department of Biomedical Engineering
Kharkiv National University of Radio Electronics
Kharkiv, Ukraine

Karina Selivanova
Department of Biomedical Engineering
Kharkiv National University of Radio
Electronics
Kharkiv, Ukraine

Oleksandr Geletka
Doctor-Neurologist of the Highest Category
\u201cLife Park\u201d Clinic

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Abstract\u2014this article explores the application of convolutional neural networks (CNNs), specifically the
\nUNet1D architecture, for filtering M-response signals \u2212 an essential component of electromyographic (EMG) diagnostics used to assess the functional state of the
\nperipheral neuromuscular system. The goal of the study is to improve signal quality by effectively removing artifacts while
\npreserving the amplitude-frequency characteristics critical for clinical interpretation. <\/p>\n","protected":false},"author":8,"featured_media":15085,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[58],"tags":[],"class_list":["post-15072","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-publications"],"yoast_head":"\nArtifact Correction Method for M-response usingUNet1D Network - DX-SYSTEMS<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dx-systems.com\/en\/artifact-correction-method-for-m-response-usingunet1d-network\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Artifact Correction Method for M-response usingUNet1D Network - DX-SYSTEMS\" \/>\n<meta property=\"og:description\" content=\"Abstract\u2014this article explores the application of convolutional neural networks (CNNs), specifically the UNet1D architecture, for filtering M-response signals \u2212 an essential component of electromyographic (EMG) diagnostics used to assess the functional state of the peripheral neuromuscular system. The goal of the study is to improve signal quality by effectively removing artifacts while preserving the amplitude-frequency characteristics critical for clinical interpretation.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dx-systems.com\/en\/artifact-correction-method-for-m-response-usingunet1d-network\/\" \/>\n<meta property=\"og:site_name\" content=\"DX-SYSTEMS\" \/>\n<meta property=\"article:published_time\" content=\"2025-12-08T12:08:00+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-06-11T11:38:11+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dx-systems.com\/wp-content\/uploads\/2026\/06\/scr-20260611-msvt.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1662\" \/>\n\t<meta property=\"og:image:height\" content=\"832\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"dx\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"dx\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/dx-systems.com\\\/en\\\/artifact-correction-method-for-m-response-usingunet1d-network\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/dx-systems.com\\\/en\\\/artifact-correction-method-for-m-response-usingunet1d-network\\\/\"},\"author\":{\"name\":\"dx\",\"@id\":\"https:\\\/\\\/dx-systems.com\\\/#\\\/schema\\\/person\\\/01c23512fcd5d05934a91a0d8f06b6b8\"},\"headline\":\"Artifact Correction Method for M-response usingUNet1D Network\",\"datePublished\":\"2025-12-08T12:08:00+00:00\",\"dateModified\":\"2026-06-11T11:38:11+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/dx-systems.com\\\/en\\\/artifact-correction-method-for-m-response-usingunet1d-network\\\/\"},\"wordCount\":38,\"publisher\":{\"@id\":\"https:\\\/\\\/dx-systems.com\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/dx-systems.com\\\/en\\\/artifact-correction-method-for-m-response-usingunet1d-network\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/dx-systems.com\\\/wp-content\\\/uploads\\\/2026\\\/06\\\/scr-20260611-msvt.png\",\"articleSection\":[\"Publications\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/dx-systems.com\\\/en\\\/artifact-correction-method-for-m-response-usingunet1d-network\\\/\",\"url\":\"https:\\\/\\\/dx-systems.com\\\/en\\\/artifact-correction-method-for-m-response-usingunet1d-network\\\/\",\"name\":\"Artifact Correction Method for M-response usingUNet1D Network - 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