{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T17:54:36Z","timestamp":1721238876144},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,9,15]]},"abstract":"<jats:p>Heart disease is the principal cause of mortality and the major contributor to reduced quality of life. The electrocardiogram is used to monitor the cardiovascular system. The correct classification of the beats in electrocardiograms gives an opportunity to have treatment more focused. The manual analysis of the ECG signals faces different problems. For this reason, automated diagnosis systems are fed by ECG signals to detect anomalies. In this paper, we propose a method based on a novel preprocessing approach and neural networks for the classification of heartbeats which is able to classify five categories of arrhythmias in accordance with the AAMI standard. The preprocessing stage allows each beat to have \u201cP wave-R peak-R peak\u201d information. We evaluated the proposed method on the MIT-BIH database, which is one of the most used databases. According to the results, the proposed approach is able to make predictions with the average accuracies of 97%. The average accuracies are compared to different approaches that use different preprocessing and classifier stages. Our approach is superior to that of most of them.<\/jats:p>","DOI":"10.3233\/faia200562","type":"book-chapter","created":{"date-parts":[[2020,9,16]],"date-time":"2020-09-16T23:02:16Z","timestamp":1600297336000},"source":"Crossref","is-referenced-by-count":1,"title":["Recognition of Heartbeat Categories Applying a Novel Preprocessing Scheme and Neural Networks"],"prefix":"10.3233","author":[{"given":"Andres","family":"Hernandez-Matamoros","sequence":"first","affiliation":[{"name":"Iwate Prefectural University (IPU), Faculty of Software and Information Science, Iwate, 020-0693, Japan"}]},{"given":"Hamido","family":"Fujita","sequence":"additional","affiliation":[{"name":"Iwate Prefectural University (IPU), Faculty of Software and Information Science, Iwate, 020-0693, Japan"}]},{"given":"Hector","family":"Perez-Meana","sequence":"additional","affiliation":[{"name":"Instituto Politecnico Nacional, Av. Santa Ana 1000 Mexico D. F., 04430, Mexico"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Knowledge Innovation Through Intelligent Software Methodologies, Tools and Techniques"],"original-title":[],"link":[{"URL":"http:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA200562","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,9,17]],"date-time":"2020-09-17T13:36:17Z","timestamp":1600349777000},"score":1,"resource":{"primary":{"URL":"http:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA200562"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,15]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia200562","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,15]]}}}