{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T12:59:41Z","timestamp":1770987581724,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,20]],"date-time":"2022-07-20T00:00:00Z","timestamp":1658275200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004504","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["01.2.2-LMT-K-718-01-0030"],"award-info":[{"award-number":["01.2.2-LMT-K-718-01-0030"]}],"id":[{"id":"10.13039\/501100004504","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The spatial QRS-T angle is a promising health indicator for risk stratification of sudden cardiac death (SCD). Thus far, the angle is estimated solely from 12-lead electrocardiogram (ECG) systems uncomfortable for ambulatory monitoring. Methods to estimate QRS-T angles from reduced-lead ECGs registered with consumer healthcare devices would, therefore, facilitate ambulatory monitoring. (1) Objective: Develop a method to estimate spatial QRS-T angles from reduced-lead ECGs. (2) Approach: We designed a deep learning model to locate the QRS and T wave vectors necessary for computing the QRS-T angle. We implemented an original loss function to guide the model in the 3D space to search for each vector\u2019s coordinates. A gradual reduction of ECG leads from the largest publicly available dataset of clinical 12-lead ECG recordings (PTB-XL) is used for training and validation. (3) Results: The spatial QRS-T angle can be estimated from leads {I, II, aVF, V2} with sufficient accuracy (absolute mean and median errors of 11.4\u00b0 and 7.3\u00b0) for detecting abnormal angles without sacrificing patient comfortability. (4) Significance: Our model could enable ambulatory monitoring of spatial QRS-T angles using patch- or textile-based ECG devices. Populations at risk of SCD, like chronic cardiac and kidney disease patients, might benefit from this technology.<\/jats:p>","DOI":"10.3390\/s22145414","type":"journal-article","created":{"date-parts":[[2022,7,21]],"date-time":"2022-07-21T03:34:40Z","timestamp":1658374480000},"page":"5414","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Deep-Learning-Based Estimation of the Spatial QRS-T Angle from Reduced-Lead ECGs"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5011-8192","authenticated-orcid":false,"given":"Ana","family":"Santos Rodrigues","sequence":"first","affiliation":[{"name":"Biomedical Engineering Institute, Kaunas University of Technology, 51423 Kaunas, Lithuania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8672-3872","authenticated-orcid":false,"given":"Rytis","family":"Augustauskas","sequence":"additional","affiliation":[{"name":"Department of Automation, Kaunas University of Technology, 51367 Kaunas, Lithuania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7963-285X","authenticated-orcid":false,"given":"Mantas","family":"Luko\u0161evi\u010dius","sequence":"additional","affiliation":[{"name":"Faculty of Informatics, Kaunas University of Technology, 51368 Kaunas, Lithuania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3434-9254","authenticated-orcid":false,"given":"Pablo","family":"Laguna","sequence":"additional","affiliation":[{"name":"Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Arag\u00f3n Institute of Engineering Research (I3A), IIS Arag\u00f3n, University of Zaragoza, 50018 Zaragoza, Spain"},{"name":"Biomedical Research Networking Center (CIBER), 50018 Zaragoza, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6879-5845","authenticated-orcid":false,"given":"Vaidotas","family":"Marozas","sequence":"additional","affiliation":[{"name":"Biomedical Engineering Institute, Kaunas University of Technology, 51423 Kaunas, Lithuania"},{"name":"Faculty of Electrical and Electronics Engineering, Kaunas University of Technology, 51367 Kaunas, Lithuania"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2222","DOI":"10.1161\/CIRCULATIONAHA.116.021306","article-title":"Global Electric Heterogeneity Risk Score for Prediction of Sudden Cardiac Death in the General Population","volume":"133","author":"Waks","year":"2016","journal-title":"Circulation"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1887","DOI":"10.1161\/CIRCRESAHA.116.304521","article-title":"The Spectrum of Epidemiology Underlying Sudden Cardiac Death","volume":"116","author":"Hayashi","year":"2015","journal-title":"Circ. 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