{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T03:51:31Z","timestamp":1769917891826,"version":"3.49.0"},"reference-count":40,"publisher":"Wiley","license":[{"start":{"date-parts":[[2021,2,2]],"date-time":"2021-02-02T00:00:00Z","timestamp":1612224000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2021,2,2]]},"abstract":"<jats:p>The incidence of cardiovascular disease is increasing year by year and is showing a younger trend. At the same time, existing medical resources are tight. The automatic detection of ECG signals becomes increasingly necessary. This paper proposes an automatic classification of ECG signals based on a dilated causal convolutional neural network. To solve the problem that the recurrent neural network framework network cannot be accelerated by hardware equipment, the dilated causal convolutional neural network is adopted. Given the features of the same input and output time steps of the recurrent neural network and the nondisclosure of future information, the network is constructed with fully convolutional networks and causal convolution. To reduce the network depth and prevent gradient explosion or gradient disappearance, the dilated factor is introduced into the model, and the residual blocks are introduced into the model according to the shortcut connection idea. The effectiveness of the algorithm is verified in the MIT-BIH Atrial Fibrillation Database (MIT-BIH AFDB). In the experiment of the MIT-BIH AFDB database, the classification accuracy rate is 98.65%.<\/jats:p>","DOI":"10.1155\/2021\/6627939","type":"journal-article","created":{"date-parts":[[2021,2,3]],"date-time":"2021-02-03T01:36:30Z","timestamp":1612316190000},"page":"1-10","source":"Crossref","is-referenced-by-count":24,"title":["An ECG Signal Classification Method Based on Dilated Causal Convolution"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6988-8023","authenticated-orcid":true,"given":"Hao","family":"Ma","sequence":"first","affiliation":[{"name":"Shandong Artificial Intelligence Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0832-8046","authenticated-orcid":true,"given":"Chao","family":"Chen","sequence":"additional","affiliation":[{"name":"Shandong Artificial Intelligence Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5441-3121","authenticated-orcid":true,"given":"Qing","family":"Zhu","sequence":"additional","affiliation":[{"name":"Qilu Hospital of Shandong University, Jinan 250012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3445-8250","authenticated-orcid":true,"given":"Haitao","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0972-3382","authenticated-orcid":true,"given":"Liming","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7136-1538","authenticated-orcid":true,"given":"Minglei","family":"Shu","sequence":"additional","affiliation":[{"name":"Shandong Artificial Intelligence Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"issue":"3","key":"1","first-page":"209","article-title":"Summary of the 2018 report on cardiovascular diseases in China","volume":"34","author":"S. 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