{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T12:30:28Z","timestamp":1780489828692,"version":"3.54.1"},"reference-count":45,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2021,8,1]],"date-time":"2021-08-01T00:00:00Z","timestamp":1627776000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Atrial fibrillation (AF) is the most common cardiovascular disease (CVD), and most existing algorithms are usually designed for the diagnosis (i.e., feature classification) or prediction of AF. Artificial intelligence (AI) algorithms integrate the diagnosis of AF electrocardiogram (ECG) and predict the possibility that AF will occur in the future. In this paper, we utilized the MIT-BIH AF Database (AFDB), which is composed of data from normal people and patients with AF and onset characteristics, and the AFPDB database (i.e., PAF Prediction Challenge Database), which consists of data from patients with Paroxysmal AF (PAF; the records contain the ECG preceding an episode of PAF), and subjects who do not have documented AF. We extracted the respective characteristics of the databases and used them in modeling diagnosis and prediction. In the aspect of model construction, we regarded diagnosis and prediction as two classification problems, adopted the traditional support vector machine (SVM) algorithm, and combined them. The improved quantum particle swarm optimization support vector machine (IQPSO-SVM) algorithm was used to speed the training time. During the verification process, the clinical FZU-FPH database created by Fuzhou University and Fujian Provincial Hospital was used for hybrid model testing. The data were obtained from the Holter monitor of the hospital and encrypted. We proposed an algorithm for transforming the PDF ECG waveform images of hospital examination reports into digital data. For the diagnosis model and prediction model trained using the training set of the AFDB and AFPDB databases, the sensitivity, specificity, and accuracy measures were 99.2% and 99.2%, 99.2% and 93.3%, and 91.7% and 92.5% for the test set of the AFDB and AFPDB databases, respectively. Moreover, the sensitivity, specificity, and accuracy were 94.2%, 79.7%, and 87.0%, respectively, when tested using the FZU-FPH database with 138 samples of the ECG composed of two labels. The composite classification and prediction model using a new water-fall ensemble method had a total accuracy of approximately 91% for the test set of the FZU-FPH database with 80 samples with 120 segments of ECG with three labels.<\/jats:p>","DOI":"10.3390\/s21155222","type":"journal-article","created":{"date-parts":[[2021,8,1]],"date-time":"2021-08-01T21:46:44Z","timestamp":1627854404000},"page":"5222","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["A Classification and Prediction Hybrid Model Construction with the IQPSO-SVM Algorithm for Atrial Fibrillation Arrhythmia"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2115-8902","authenticated-orcid":false,"given":"Liang-Hung","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ze-Hong","family":"Yan","sequence":"additional","affiliation":[{"name":"Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi-Ting","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun-Ying","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"I-Chun","family":"Kuo","sequence":"additional","affiliation":[{"name":"Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8848-6644","authenticated-orcid":false,"given":"Patricia Angela R.","family":"Abu","sequence":"additional","affiliation":[{"name":"Department of Information Systems and Computer Science, Ateneo de Manila University, Quezon 1108, Philippines"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pao-Cheng","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7605-5214","authenticated-orcid":false,"given":"Chiung-An","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Ming Chi University of Technology, New Taipei 243303, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4079-9350","authenticated-orcid":false,"given":"Shih-Lun","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Chung Yuan Christian University, Taoyuan 320314, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,1]]},"reference":[{"key":"ref_1","unstructured":"Alonso, A., Almuwaqqat, Z., and Chamberlain, A. 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