Introduction to electrocardiogram signal quality assessment and estimated accuracy for textile electrodes

Introduction to electrocardiogram signal quality assessment and estimated accuracy for textile electrodes | 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 Introduction to electrocardiogram signal quality assessment and estimated accuracy for textile electrodes Neusa Adão Martins, Frederik Bauer, Florent Baty, Maximilian Boesch, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5804513/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract As the use of wearable electrocardiogram (ECG) data for modeling purposes continues to rise, there is a pressing need for signal quality assessment (SQA) algorithms capable of identifying segments of signal from which reliable data can be obtained. Manually annotated ECG data, obtained through expert visual inspection, is often used as reference in the development of ECG SQA algorithms. In this approach, the quality of a signal segment is assessed based on the level of noise present. Yet, the data extracted from noise-corrupted ECG signal segments might still be of sufficient accuracy depending on the target application.The current work proposes a paradigm shift by presenting a SQA algorithm that performs template matching and physiological feasibility checks to determine the quality of ECG signals acquired by textile-based wearable systems. Signal segments were classified into four different quality classes based on the estimated accuracy of RR intervals extracted from the signal segments of each class. Our findings show that the proposed SQA algorithm is effective in identifying ECG signal segments from which accurate RR intervals can be derived, and that the proportion of the data across the different classes is sensitive to different factors known to have an effect on signal quality. Health sciences/Diseases/Neurological disorders/Sleep disorders Physical sciences/Mathematics and computing/Computer science Physical sciences/Materials science/Materials for devices/Sensors and biosensors Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Full Text Additional Declarations No competing interests reported. ethics approval for each dataset used in our study: Dataset 1: Ethical clearance was obtained from the ethics committee of Kanton St. Gallen, Switzerland (EKOS 15/140), and all patients gave their written informed consent to participate in the study. Dataset 2: Ethical clearance was obtained from the ethics committee of Kanton St. Gallen, Switzerland (EKOS 19/038), and all patients gave their written informed consent to participate in the study. Dataset 3: The study was conducted for the internal testing of measuring devices, and the study protocol was approved by the local institutional review board. All patients gave their written informed consent to participate in the study. Supplementary Files SupplementaryInformation.pdf Cite Share Download PDF Status: Published Journal Publication published 21 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 10 Apr, 2025 Reviews received at journal 21 Feb, 2025 Reviews received at journal 04 Feb, 2025 Reviewers agreed at journal 29 Jan, 2025 Reviewers agreed at journal 26 Jan, 2025 Reviewers agreed at journal 24 Jan, 2025 Reviewers invited by journal 24 Jan, 2025 Editor assigned by journal 24 Jan, 2025 Editor invited by journal 13 Jan, 2025 Submission checks completed at journal 13 Jan, 2025 First submitted to journal 10 Jan, 2025 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-5804513","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":441010972,"identity":"570870c5-7ba8-4eea-9ded-60f692074ec2","order_by":0,"name":"Neusa Adão Martins","email":"","orcid":"","institution":"Swiss Federal Laboratories for Materials Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Neusa","middleName":"Adão","lastName":"Martins","suffix":""},{"id":441010973,"identity":"81dc24e6-7835-4714-b12d-d4098c1a151c","order_by":1,"name":"Frederik Bauer","email":"","orcid":"","institution":"Swiss Federal Laboratories for Materials Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Frederik","middleName":"","lastName":"Bauer","suffix":""},{"id":441010974,"identity":"daea34a6-ab4c-4394-ada0-11adb788a961","order_by":2,"name":"Florent Baty","email":"","orcid":"","institution":"Kantonsspital St. Gallen","correspondingAuthor":false,"prefix":"","firstName":"Florent","middleName":"","lastName":"Baty","suffix":""},{"id":441010975,"identity":"e3d0ea01-b363-48c3-b8fd-a02bf7ffe6cc","order_by":3,"name":"Maximilian Boesch","email":"","orcid":"","institution":"Kantonsspital St. Gallen","correspondingAuthor":false,"prefix":"","firstName":"Maximilian","middleName":"","lastName":"Boesch","suffix":""},{"id":441010976,"identity":"7314d097-a718-44ee-bb87-b5131aeec240","order_by":4,"name":"Martin Brutsche","email":"","orcid":"","institution":"Kantonsspital St. Gallen","correspondingAuthor":false,"prefix":"","firstName":"Martin","middleName":"","lastName":"Brutsche","suffix":""},{"id":441010977,"identity":"0b59314a-cd7d-476d-9386-079df9224330","order_by":5,"name":"René Rossi","email":"","orcid":"","institution":"Swiss Federal Laboratories for Materials Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"René","middleName":"","lastName":"Rossi","suffix":""},{"id":441010978,"identity":"5469790b-d30f-4c3d-af66-55e3c7b5f19f","order_by":6,"name":"Simon Annaheim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYDACZjiLh4EhgcEGwmZsIF5LGhFaEIAHRBwmrEW+nTvxcQGDXZ45+9mDDx7mnJfTnd38gOHnDtxaDA7zbjaewZBcbNmTl2yQuO22sdmdYwaMvWfwaGHm3SbNw8CcuOFAjpkEUEvithsJBsyMbXgc1gzWUp+44fwb8x+J287Vb7uR/gGvFobDYC2HEzfcyDFjSNx2IMHsRg5+W8B+4TE4DtTyxhjosGTDbXfOFBzsxeew/rMbH/NUVAMdlmP48ec2O3mz2+0bH/zE5zCIXcgcCQaGA4Q0oAEJEtWPglEwCkbBsAcAYUhT0o8mVMMAAAAASUVORK5CYII=","orcid":"","institution":"Swiss Federal Laboratories for Materials Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Simon","middleName":"","lastName":"Annaheim","suffix":""}],"badges":[],"createdAt":"2025-01-10 14:38:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5804513/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5804513/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-25365-x","type":"published","date":"2025-11-21T15:58:38+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83262127,"identity":"92ff94fd-3feb-4ed2-9e79-58ad00e61e17","added_by":"auto","created_at":"2025-05-22 04:13:36","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":90683,"visible":true,"origin":"","legend":"\u003cp\u003eAnnotated PQRST complex. The timing of the R-peak is defined as zero.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5804513/v1/c0e3a82e8c08ff66cd80237d.jpg"},{"id":83262132,"identity":"7ae9ad16-363d-4b73-bb4c-2c861d5cd0cd","added_by":"auto","created_at":"2025-05-22 04:13:37","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1020642,"visible":true,"origin":"","legend":"\u003cp\u003eSingle QRS and PQRST complexes (blue) of a segment aligned on their R peak at T\u003csub\u003e0\u003c/sub\u003e. The individual template complex for each segment (red) was calculated by taking the mean of all individual complexes. The mean Pearson correlation coefficient (r) was calculated based on correlations of single complexes and the template. The QRS and PQRST complexes of the upper (a,b) and lower two figures (c, d) originate from the same segment, respectively.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5804513/v1/8bbf01a2f3089b3d30563198.jpg"},{"id":83262319,"identity":"d433255d-7605-47fc-babb-c57314574dee","added_by":"auto","created_at":"2025-05-22 04:21:36","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":224103,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of data across quality classes: (a) for the multi-parameter monitoring belt (Belt) and gel electrodes (Gel) in the inpatient setting (n = 42); (b) the multi-parameter monitoring belt in both outpatient (Home) and inpatient (Hosp) settings (n = 32). Data from Dataset 2. The asterisks indicate significance in the Wilcoxon signed rank test: * – p \u0026lt; 0.05, ** – p \u0026lt; 0.01, *** – p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5804513/v1/4b4b6f2c8f921c9721fa4f69.jpg"},{"id":83262130,"identity":"beed4edc-b63c-46ac-b061-3ee16dd62805","added_by":"auto","created_at":"2025-05-22 04:13:37","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":384966,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between body position and signal quality: (a) Multi-parameter monitoring belt in the inpatient setting; (b) Multi-parameter monitoring belt in the outpatient setting. Data represent the median cumulative proportion of data for all subjects across quality classes: Class 1 (proportion of Class 1), Class 2 (cumulative proportion of Classes 1 and 2), Class 3 (cumulative proportion of Classes 1 to 3), and Class 4 (cumulative proportion across all classes). Data from Dataset 2.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5804513/v1/b4d2b9887084657dc9979d6b.jpg"},{"id":83262128,"identity":"54ae551e-1896-489d-a103-fb236239b8da","added_by":"auto","created_at":"2025-05-22 04:13:36","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":79807,"visible":true,"origin":"","legend":"\u003cp\u003eInfluence of body movement on signal quality - relationship between jerk and the proportion data in quality classes.\u003c/p\u003e\n\u003cp\u003eData from Dataset 2.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-5804513/v1/07a272379db820063d1ad4dc.png"},{"id":83262779,"identity":"646b7b68-0724-4f00-84ba-36c8532db10e","added_by":"auto","created_at":"2025-05-22 04:29:36","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":27558,"visible":true,"origin":"","legend":"\u003cp\u003eInfluence of ECG monitoring belt electrode usage on signal quality. Data from Dataset 1.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-5804513/v1/9976ce19ad0b2cb2d809ee0d.png"},{"id":96651076,"identity":"7f3708fa-af5f-4046-913d-ec001fea8e1f","added_by":"auto","created_at":"2025-11-24 16:13:43","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2153760,"visible":true,"origin":"","legend":"","description":"","filename":"hwdhgcrshhndhnbrswfnvthtbgtnbzjq.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5804513/v1_covered_234c76b5-650c-4c2e-ba58-3560d8c7dfe0.pdf"},{"id":83262126,"identity":"6c4951bc-301a-42fb-8d09-1ca14f8c6370","added_by":"auto","created_at":"2025-05-22 04:13:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":271602,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5804513/v1/323a5339027716701ef97d23.pdf"}],"financialInterests":"\u003cp\u003eNo competing interests reported.\u003c/p\u003e\n\u003cp\u003eethics approval for each dataset used in our study: Dataset 1: Ethical clearance was obtained from the ethics committee of Kanton St. Gallen, Switzerland (EKOS 15/140), and all patients gave their written informed consent to participate in the study. Dataset 2: Ethical clearance was obtained from the ethics committee of Kanton St. Gallen, Switzerland (EKOS 19/038), and all patients gave their written informed consent to participate in the study. Dataset 3: The study was conducted for the internal testing of measuring devices, and the study protocol was approved by the local institutional review board. All patients gave their written informed consent to participate in the study.\u003c/p\u003e","formattedTitle":" Introduction to electrocardiogram signal quality assessment and estimated accuracy for textile electrodes","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5804513/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5804513/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"As the use of wearable electrocardiogram (ECG) data for modeling purposes continues to rise, there is a pressing need for signal quality assessment (SQA) algorithms capable of identifying segments of signal from which reliable data can be obtained. Manually annotated ECG data, obtained through expert visual inspection, is often used as reference in the development of ECG SQA algorithms. In this approach, the quality of a signal segment is assessed based on the level of noise present. Yet, the data extracted from noise-corrupted ECG signal segments might still be of sufficient accuracy depending on the target application.The current work proposes a paradigm shift by presenting a SQA algorithm that performs template matching and physiological feasibility checks to determine the quality of ECG signals acquired by textile-based wearable systems. Signal segments were classified into four different quality classes based on the estimated accuracy of RR intervals extracted from the signal segments of each class. Our findings show that the proposed SQA algorithm is effective in identifying ECG signal segments from which accurate RR intervals can be derived, and that the proportion of the data across the different classes is sensitive to different factors known to have an effect on signal quality.","manuscriptTitle":" Introduction to electrocardiogram signal quality assessment and estimated accuracy for textile electrodes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-22 04:13:32","doi":"10.21203/rs.3.rs-5804513/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-10T07:28:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-21T18:34:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-04T19:48:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6292110022646167555892094117516635122","date":"2025-01-29T14:22:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54481451659843569732184749379561330481","date":"2025-01-26T16:16:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"152852726555878557912003163202794748830","date":"2025-01-24T15:14:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-01-24T14:19:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-24T14:14:34+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-01-13T12:13:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-01-13T12:05:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-01-10T14:24:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"16c24ff3-a13c-487a-8d51-10d01e083531","owner":[],"postedDate":"May 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46954753,"name":"Health sciences/Diseases/Neurological disorders/Sleep disorders"},{"id":46954754,"name":"Physical sciences/Mathematics and computing/Computer science"},{"id":46954755,"name":"Physical sciences/Materials science/Materials for devices/Sensors and biosensors"}],"tags":[],"updatedAt":"2025-11-24T16:11:46+00:00","versionOfRecord":{"articleIdentity":"rs-5804513","link":"https://doi.org/10.1038/s41598-025-25365-x","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-11-21 15:58:38","publishedOnDateReadable":"November 21st, 2025"},"versionCreatedAt":"2025-05-22 04:13:32","video":"","vorDoi":"10.1038/s41598-025-25365-x","vorDoiUrl":"https://doi.org/10.1038/s41598-025-25365-x","workflowStages":[]},"version":"v1","identity":"rs-5804513","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5804513","identity":"rs-5804513","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}