{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T00:57:25Z","timestamp":1764723445915,"version":"3.46.0"},"reference-count":73,"publisher":"Springer Science and Business Media LLC","issue":"16","license":[{"start":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T00:00:00Z","timestamp":1763337600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T00:00:00Z","timestamp":1763337600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s11760-025-04960-5","type":"journal-article","created":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T14:54:24Z","timestamp":1763391264000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Arrhythmia detection from 12-Lead ECG with 2-phase feature extraction: by presenting the evaluation of atrial fibrillation"],"prefix":"10.1007","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9347-9775","authenticated-orcid":false,"given":"Gizemnur","family":"Erol Do\u011fan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1698-0106","authenticated-orcid":false,"given":"G\u00fclay","family":"Tezel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5035-7575","authenticated-orcid":false,"given":"Fatma Zehra","family":"Solak","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0255-5988","authenticated-orcid":false,"given":"Bet\u00fcl","family":"Uzba\u015f","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,11,17]]},"reference":[{"issue":"1","key":"4960_CR1","doi-asserted-by":"publisher","first-page":"3","DOI":"10.4330\/wjc.v1.i1.3","volume":"1","author":"TO Aje","year":"2009","unstructured":"Aje, T.O., Miller, M.: Cardiovascular disease: A global problem extending into the developing world. World J. Cardiol. 1(1), 3\u201310 (2009). https:\/\/doi.org\/10.4330\/wjc.v1.i1.3","journal-title":"World J. Cardiol."},{"issue":"6","key":"4960_CR2","doi-asserted-by":"publisher","first-page":"901","DOI":"10.1016\/j.yjmcc.2010.09.005","volume":"49","author":"LF Santana","year":"2010","unstructured":"Santana, L.F., Cheng, E.P., Lederer, W.J.: How does the shape of the cardiac action potential control calcium signaling and contraction in the heart? J. Mol. Cell. Cardiol. 49(6), 901\u2013903 (2010). https:\/\/doi.org\/10.1016\/j.yjmcc.2010.09.005","journal-title":"J. Mol. Cell. Cardiol."},{"issue":"4","key":"4960_CR3","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/j.irbm.2019.12.001","volume":"41","author":"S Sahoo","year":"2020","unstructured":"Sahoo, S., Dash, M., Behera, S., Sabut, S.: Machine learning approach to detect cardiac arrhythmias in ECG signals: A survey. IRBM. 41(4), 185\u2013194 (2020). https:\/\/doi.org\/10.1016\/j.irbm.2019.12.001","journal-title":"IRBM"},{"key":"4960_CR4","unstructured":"World Health Organization (WHO): Cardiovascular diseases. (2023). https:\/\/www.who.int\/health-topics\/cardiovascular-diseases#tab=tab_1"},{"issue":"2","key":"4960_CR5","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1016\/j.aogh.2016.04.002","volume":"82","author":"R Gupta","year":"2016","unstructured":"Gupta, R., Mohan, I., Narula, J.: Trends in coronary heart disease epidemiology in India. Ann. Glob Health. 82(2), 307\u2013315 (2016). https:\/\/doi.org\/10.1016\/j.aogh.2016.04.002","journal-title":"Ann. Glob Health"},{"issue":"9","key":"4960_CR6","doi-asserted-by":"publisher","first-page":"818","DOI":"10.1056\/NEJMoa1311890","volume":"371","author":"S Yusuf","year":"2014","unstructured":"Yusuf, S., Rangarajan, S., Teo, K., Islam, S., Li, W., Liu, L., Dagenais, G.: Cardiovascular risk and events in 17 low-, middle-, and high-income countries. N Engl. J. Med. 371(9), 818\u2013827 (2014). https:\/\/doi.org\/10.1056\/NEJMoa1311890","journal-title":"N Engl. J. Med."},{"issue":"16","key":"4960_CR7","doi-asserted-by":"publisher","first-page":"1605","DOI":"10.1161\/CIRCULATIONAHA.114.008729","volume":"133","author":"D Prabhakaran","year":"2016","unstructured":"Prabhakaran, D., Jeemon, P., Roy, A.: Cardiovascular diseases in india: Current epidemiology and future direction. Circulation. 133(16), 1605\u20131620 (2016). https:\/\/doi.org\/10.1161\/CIRCULATIONAHA.114.008729","journal-title":"Circulation"},{"issue":"9","key":"4960_CR8","doi-asserted-by":"publisher","first-page":"1216","DOI":"10.1161\/CIRCULATIONAHA.107.717033","volume":"117","author":"HC McGill","year":"2008","unstructured":"McGill, H.C., McMahan, C.A., Gidding, S.S.: Preventing heart disease in the 21st century: Implications of the pathobiological determinants of atherosclerosis in youth (PDAY) study. Circulation. 117(9), 1216\u20131227 (2008). https:\/\/doi.org\/10.1161\/CIRCULATIONAHA.107.717033","journal-title":"Circulation"},{"key":"4960_CR9","doi-asserted-by":"publisher","DOI":"10.5772\/65620","author":"P Ganesan","year":"2016","unstructured":"Ganesan, P., Sterling, M., Ladavich, S., Ghoraani, B.: Computer-aided clinical decision support systems for atrial fibrillation. Computer-Aided Technol. - Appl. Eng. Med. (2016). https:\/\/doi.org\/10.5772\/65620","journal-title":"Computer-Aided Technol. - Appl. Eng. Med."},{"key":"4960_CR10","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.jbi.2015.11.007","volume":"59","author":"A Alberdi","year":"2016","unstructured":"Alberdi, A., Aztiria, A., Basarab, A.: Towards an automatic early stress recognition system for office environments based on multimodal measurements: A review. J. Biomed. Inf. 59, 49\u201375 (2016). https:\/\/doi.org\/10.1016\/j.jbi.2015.11.007","journal-title":"J. Biomed. Inf."},{"issue":"2","key":"4960_CR11","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1007\/s13534-021-00185-w","volume":"11","author":"M Rashed-Al-Mahfuz","year":"2021","unstructured":"Rashed-Al-Mahfuz, M., Moni, M.A., Lio, P., Islam, S.M.S., Berkovsky, S., Khushi, M., Quinn, J.M.W.: Deep convolutional neural networks based ECG beats classificatsion to diagnose cardiovascular conditions. Biomed. Eng. Lett. 11(2), 147\u2013162 (2021). https:\/\/doi.org\/10.1007\/s13534-021-00185-w","journal-title":"Biomed. Eng. Lett."},{"key":"4960_CR12","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/j.eswa.2016.09.030","volume":"67","author":"M Merone","year":"2017","unstructured":"Merone, M., Soda, P., Sansone, M., Sansone, C.: ECG databases for biometric systems: A systematic review. Expert Syst. Appl. 67, 189\u2013202 (2017). https:\/\/doi.org\/10.1016\/j.eswa.2016.09.030","journal-title":"Expert Syst. Appl."},{"issue":"1","key":"4960_CR13","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1007\/BF02637023","volume":"34","author":"P Laguna","year":"1996","unstructured":"Laguna, P., Jan\u00e9, R., Olmos, S., Thakor, N.V., Rix, H., Caminal, P.: Adaptive estimation of QRS complex wave features of ECG signal by the Hermite model. Med. Biol. Eng. Comput. 34(1), 58\u201368 (1996). https:\/\/doi.org\/10.1007\/BF02637023","journal-title":"Med. Biol. Eng. Comput."},{"key":"4960_CR14","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.patrec.2015.11.018","volume":"70","author":"RG Afkhami","year":"2016","unstructured":"Afkhami, R.G., Azarnia, G., Tinati, M.A.: Cardiac arrhythmia classification using statistical and mixture modeling features of ECG signals. Pattern Recogn. Lett. 70, 45\u201351 (2016). https:\/\/doi.org\/10.1016\/j.patrec.2015.11.018","journal-title":"Pattern Recogn. Lett."},{"issue":"4","key":"4960_CR15","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1109\/TCE.2018.2875799","volume":"64","author":"S Lee","year":"2018","unstructured":"Lee, S., Huang, P., Liang, M., Liang, M.C., Hong, J.H.: Development of an arrhythmia monitoring system and human study. IEEE Trans. Consum. Electron. 64(4), 442\u2013451 (2018). https:\/\/doi.org\/10.1109\/TCE.2018.2875799","journal-title":"IEEE Trans. Consum. Electron."},{"issue":"5","key":"4960_CR16","doi-asserted-by":"publisher","first-page":"554","DOI":"10.1109\/LSP.2014.2308591","volume":"21","author":"AG Ramakrishnan","year":"2014","unstructured":"Ramakrishnan, A.G., Prathosh, A.P., Ananthapadmanabha, T.V.: Threshold-independent QRS detection using the dynamic plosion index. IEEE Signal. Process. Lett. 21(5), 554\u2013558 (2014). https:\/\/doi.org\/10.1109\/LSP.2014.2308591","journal-title":"IEEE Signal. Process. Lett."},{"issue":"6","key":"4960_CR17","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1109\/LSP.2016.2531996","volume":"23","author":"SJ Kang","year":"2016","unstructured":"Kang, S.J., Lee, S.Y., Cho, H.I., Park, H.: ECG authentication system design based on signal analysis in mobile and wearable devices. IEEE Signal. Process. Lett. 23(6), 805\u2013808 (2016). https:\/\/doi.org\/10.1109\/LSP.2016.2531996","journal-title":"IEEE Signal. Process. Lett."},{"key":"4960_CR18","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/j.jelectrocard.2021.04.016","volume":"64","author":"X Yang","year":"2021","unstructured":"Yang, X., Zhang, X., Yang, M., Zhang, L.: 12-lead ECG arrhythmia classification using cascaded convolutional neural network and expert feature. J. Electrocardiol. 64, 56\u201362 (2021). https:\/\/doi.org\/10.1016\/j.jelectrocard.2021.04.016","journal-title":"J. Electrocardiol."},{"issue":"10","key":"4960_CR19","doi-asserted-by":"publisher","first-page":"1306","DOI":"10.1161\/CIRCULATIONAHA.106.180200","volume":"115","author":"P Kligfield","year":"2007","unstructured":"Kligfield, P., Gettes, L.S., Bailey, J.J., Childers, R., Deal, B.J., Hancock, E.W., Wagner, G.S.: Recommendations for the standardization and interpretation of the electrocardiogram. Circulation. 115(10), 1306\u20131324 (2007). https:\/\/doi.org\/10.1161\/CIRCULATIONAHA.106.180200","journal-title":"Circulation"},{"issue":"9","key":"4960_CR20","doi-asserted-by":"publisher","first-page":"1183","DOI":"10.1016\/j.jacc.2017.07.723","volume":"70","author":"J Schlapfer","year":"2017","unstructured":"Schlapfer, J., Wellens, H.J.: Computer-interpreted electrocardiograms. J. Am. Coll. Cardiol. 70(9), 1183\u20131192 (2017). https:\/\/doi.org\/10.1016\/j.jacc.2017.07.723","journal-title":"J. Am. Coll. Cardiol."},{"issue":"7","key":"4960_CR21","doi-asserted-by":"publisher","first-page":"1196","DOI":"10.1109\/TBME.2004.827359","volume":"51","author":"P De Chazal","year":"2004","unstructured":"De Chazal, P., O\u2019Dwyer, M., Reilly, R.B.: Automatic classification of heartbeats using ECG morphology and heartbeat interval features. IEEE Trans. Biomed. Eng. 51(7), 1196\u20131206 (2004). https:\/\/doi.org\/10.1109\/TBME.2004.827359","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"3","key":"4960_CR22","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1109\/51.932724","volume":"20","author":"GB Moody","year":"2001","unstructured":"Moody, G.B., Mark, R.G.: The impact of the MIT-BIH arrhythmia database. IEEE Eng. Med. Biol. 20(3), 45\u201350 (2001). https:\/\/doi.org\/10.1109\/51.932724","journal-title":"IEEE Eng. Med. Biol."},{"key":"4960_CR23","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1016\/j.compbiomed.2017.08.022","volume":"87","author":"UR Acharya","year":"2017","unstructured":"Acharya, U.R., Oh, S.L., Hagiwara, Y.: A deep convolutional neural network model to classify heartbeats. Comput. Biol. Med. 87, 389\u2013396 (2017). https:\/\/doi.org\/10.1016\/j.compbiomed.2017.08.022","journal-title":"Comput. Biol. Med."},{"key":"4960_CR24","doi-asserted-by":"publisher","first-page":"268","DOI":"10.1016\/j.procs.2017.11.238","volume":"120","author":"A Isin","year":"2017","unstructured":"Isin, A., \u00d6zdalili, S.: Cardiac arrhythmia detection using deep learning. Procedia Comput. Sci. 120, 268\u2013275 (2017). https:\/\/doi.org\/10.1016\/j.procs.2017.11.238","journal-title":"Procedia Comput. Sci."},{"key":"4960_CR25","doi-asserted-by":"publisher","first-page":"446","DOI":"10.1016\/j.future.2018.03.057","volume":"86","author":"G Sannino","year":"2018","unstructured":"Sannino, G., Pietro, G.D.: A deep learning approach for ECG-based heartbeat classification for arrhythmia detection. Future Gener Comput. Syst. 86, 446\u2013455 (2018). https:\/\/doi.org\/10.1016\/j.future.2018.03.057","journal-title":"Future Gener Comput. Syst."},{"issue":"22","key":"4960_CR26","doi-asserted-by":"publisher","first-page":"5450","DOI":"10.3390\/jcm10225450","volume":"10","author":"M Sraitih","year":"2021","unstructured":"Sraitih, M., Jabrane, Y., Hassani, E.: An automated system for ECG arrhythmia detection using machine learning techniques. J. Clin. Med. 10(22), 5450 (2021). https:\/\/doi.org\/10.3390\/jcm10225450","journal-title":"J. Clin. Med."},{"key":"4960_CR27","doi-asserted-by":"publisher","unstructured":"Soualhi, K., Elloumi Oueslati, A., Ellouze, N.: ECG image representation of normal sinus rhythm. In: Proc. 1st Int. Conf. Advanced Technologies for Signal and Image Processing (ATSIP), 225\u2013230 (2014). https:\/\/doi.org\/10.1109\/ATSIP.2014.6834611","DOI":"10.1109\/ATSIP.2014.6834611"},{"key":"4960_CR28","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1016\/j.compeleceng.2015.12.015","volume":"53","author":"J Mateo","year":"2016","unstructured":"Mateo, J., Torres, A.M., Aparicio, A., Santos, J.L.: An efficient method for ECG beat classification and correction of ectopic beats. Comput. Electr. Eng. 53, 219\u2013229 (2016). https:\/\/doi.org\/10.1016\/j.compeleceng.2015.12.015","journal-title":"Comput. Electr. Eng."},{"key":"4960_CR29","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.bspc.2015.10.008","volume":"25","author":"S Shadmand","year":"2016","unstructured":"Shadmand, S., Mashoufi, B.: A new personalized ECG signal classification algorithm using block-based neural network and particle swarm optimization. Biomed. Signal. Process. Control. 25, 12\u201323 (2016). https:\/\/doi.org\/10.1016\/j.bspc.2015.10.008","journal-title":"Biomed. Signal. Process. Control"},{"key":"4960_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2015.12.008","author":"EJD Luz","year":"2016","unstructured":"Luz, E.J.D., Schwartz, W.R., Camara-Chavez, G., Menotti, D.: ECG-based heartbeat classification for arrhythmia detection: A survey. Comput. Methods Programs Biomed. (2016). https:\/\/doi.org\/10.1016\/j.cmpb.2015.12.008","journal-title":"Comput. Methods Programs Biomed."},{"key":"4960_CR31","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-020-0386-x","author":"J Zheng","year":"2020","unstructured":"Zheng, J., Zhang, J., Danioko, S., Yao, H., Guo, H., Rakovski, C.: A 12-Lead electrocardiogram database for arrhythmia research covering more than 10,000 patients. Sci. Data. (2020). https:\/\/doi.org\/10.1038\/s41597-020-0386-x","journal-title":"Sci. Data"},{"key":"4960_CR32","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.1985.325532","author":"J Pan","year":"1985","unstructured":"Pan, J., Tompkins, W.J.: A real-time QRS detection algorithm. IEEE Trans. Biomed. Eng. (1985). https:\/\/doi.org\/10.1109\/TBME.1985.325532","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"4960_CR33","doi-asserted-by":"publisher","DOI":"10.3389\/fped.2022.917730","author":"M Wang","year":"2022","unstructured":"Wang, M., Xu, Y., Wang, S., Zhao, T., Cai, H., Wang, Y., Zou, R., Wang, C.: Predictive value of electrocardiographic markers in children with dilated cardiomyopathy. Front. Pediatr. (2022). https:\/\/doi.org\/10.3389\/fped.2022.917730","journal-title":"Front. Pediatr."},{"issue":"2","key":"4960_CR34","doi-asserted-by":"publisher","first-page":"227","DOI":"10.3390\/healthcare9020227","volume":"9","author":"L Wu","year":"2021","unstructured":"Wu, L., Xie, X., Wang, Y.: ECG enhancement and R-Peak detection based on window variability. Healthcare. 9(2), 227 (2021). https:\/\/doi.org\/10.3390\/healthcare9020227","journal-title":"Healthcare"},{"key":"4960_CR35","doi-asserted-by":"publisher","unstructured":"Chen, L.Y., Ribeiro, A.L.P., Platonov, P.G., Cygankiewicz, I., Soliman, E.Z., Gorenek, B., Ikeda, T., Vassilikos, V.P., Steinberg, J.S., Varma, N., Bay\u00e9s-de-Luna, A., Baranchuk, A.: P wave parameters and indices: A critical appraisal of clinical utility, challenges, and future research\u2014A consensus document endorsed by the International Society of Electrocardiology and the International Society for Holter and Noninvasive Electrocardiology. Circulation: Arrhythmia and Electrophysiology. 15(4):e010435 (2022). https:\/\/doi.org\/10.1161\/CIRCEP.121.010435","DOI":"10.1161\/CIRCEP.121.010435"},{"issue":"1","key":"4960_CR36","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.hrthm.2009.09.024","volume":"7","author":"ME Lemmert","year":"2010","unstructured":"Lemmert, M.E., Majidi, M., Krucoff, M.W., Bekkers, S.C.A.M., Crijns, H.J.G.M., Wellens, H.J.J., Kosinski, A.S., Gorgels, A.P.M.: RR-interval irregularity precedes ventricular fibrillation in ST elevation acute myocardial infarction. Heart Rhythm. 7(1), 65\u201371 (2010). https:\/\/doi.org\/10.1016\/j.hrthm.2009.09.024","journal-title":"Heart Rhythm"},{"issue":"1","key":"4960_CR37","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.hrthm.2013.10.044","volume":"11","author":"A Alonso","year":"2014","unstructured":"Alonso, A., Chen, L.Y.: PR interval, P-wave duration, and mortality: New insights, additional questions. Heart Rhythm. 11(1), 99\u2013100 (2014). https:\/\/doi.org\/10.1016\/j.hrthm.2013.10.044","journal-title":"Heart Rhythm"},{"key":"4960_CR38","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1105575","author":"JS Healey","year":"2012","unstructured":"Healey, J.S., Connolly, S.J., Gold, M.R., Israel, C.W., Gelder, I.C.V., Capucci, A., Hohnloser, S.H.: Subclinical atrial fibrillation and the risk of stroke. N Engl. J. Med. (2012). https:\/\/doi.org\/10.1056\/NEJMoa1105575","journal-title":"N Engl. J. Med."},{"key":"4960_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2019.103378","author":"W Cai","year":"2020","unstructured":"Cai, W., Chen, Y., Guo, J., Han, B., Shi, Y., Ji, L.: Accurate detection of atrial fibrillation from 12-Lead ECG using deep neural network. Comput. Biol. Med. (2020). https:\/\/doi.org\/10.1016\/j.compbiomed.2019.103378","journal-title":"Comput. Biol. Med."},{"key":"4960_CR40","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.eurheartj.a060332","author":"A Taddei","year":"1992","unstructured":"Taddei, A., Distante, G., Emdin, M., Pisani, P., Moody, G.B., Zeelenberg, C., Marchesi, C.: The European ST-T database: Standard for evaluating systems for the analysis of ST-T changes in ambulatory electrocardiography. Eur. Heart J. (1992). https:\/\/doi.org\/10.1093\/oxfordjournals.eurheartj.a060332","journal-title":"Eur. Heart J."},{"key":"4960_CR41","doi-asserted-by":"publisher","DOI":"10.1161\/01.cir.101.23.e215","author":"AL Goldberger","year":"2000","unstructured":"Goldberger, A.L., Amaral, L.A., Glass, L., Hausdorff, J.M., Ivanov, P.C., Mark, R.G.: Physiobank, physiotoolkit, and physionet: Components of a new research resource for complex physiologic signals. Circulation. (2000). https:\/\/doi.org\/10.1161\/01.cir.101.23.e215","journal-title":"Circulation"},{"key":"4960_CR42","doi-asserted-by":"publisher","DOI":"10.1109\/10.362922","author":"C Li","year":"1995","unstructured":"Li, C., Zheng, C., Tai, C.: Detection of ECG characteristic points using wavelet transforms. IEEE Trans. Biomed. Eng. (1995). https:\/\/doi.org\/10.1109\/10.362922","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"4960_CR43","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-59821-7","author":"J Zheng","year":"2020","unstructured":"Zheng, J., Chu, H., Struppa, D., Zhang, J., Yacoub, S.M., El-Askary, H., Rakovski, C.: Optimal multi-stage arrhythmia classification approach. Sci. Rep. (2020). https:\/\/doi.org\/10.1038\/s41598-020-59821-7","journal-title":"Sci. Rep."},{"key":"4960_CR44","unstructured":"Butterworth, S.: On the theory of filter amplifiers. Experimental Wireless and the Wireless Engineer. 7:536\u2013541 (1930)"},{"key":"4960_CR45","doi-asserted-by":"crossref","unstructured":"Cleveland, W.S.: Robust locally weighted regression and smoothing scatterplots. JASA. 74(368), 829\u2013836 (1979)","DOI":"10.1080\/01621459.1979.10481038"},{"key":"4960_CR46","doi-asserted-by":"crossref","unstructured":"Cleveland, S., Devlin, J.: Locally weighted regression: An approach to regression analysis by local fitting. JASA. 83(403), 596\u2013610 (1988)","DOI":"10.1080\/01621459.1988.10478639"},{"key":"4960_CR47","unstructured":"Kumar, A.: ECG-simplified. CBS Publishers Distributors Pvt Ltd. India (2010)"},{"key":"4960_CR48","doi-asserted-by":"crossref","unstructured":"Vieau, S., Iaizzo, P.A.: Basic ECG theory, 12-Lead recordings, and their interpretation. Handbook of Cardiac Anatomy, Physiology, and Devices (2015)","DOI":"10.1007\/978-3-319-19464-6_19"},{"key":"4960_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2015.03.005","author":"S Asgari","year":"2015","unstructured":"Asgari, S., Mehrnia, A., Moussavi, M.: Automatic detection of atrial fibrillation using stationary wavelet transform and support vector machine. Comput. Biol. Med. (2015). https:\/\/doi.org\/10.1016\/j.compbiomed.2015.03.005","journal-title":"Comput. Biol. Med."},{"key":"4960_CR50","doi-asserted-by":"publisher","DOI":"10.1007\/BF02347697a","author":"L Clavier","year":"2002","unstructured":"Clavier, L., Boucher, J.M., Lepage, R., Blanc, J.J., Cornily, J.C.: Automatic P-wave analysis of patients prone to atrial fibrillation. Med. Biol. Eng. Comput. (2002). https:\/\/doi.org\/10.1007\/BF02347697a","journal-title":"Med. Biol. Eng. Comput."},{"key":"4960_CR51","doi-asserted-by":"publisher","DOI":"10.1007\/s10439-009-9740-z","author":"S Dash","year":"2009","unstructured":"Dash, S., Chon, K., Lu, S., Raeder, E.A.: Automatic real-time detection of atrial fibrillation. Ann. Biomed. Eng. (2009). https:\/\/doi.org\/10.1007\/s10439-009-9740-z","journal-title":"Ann. Biomed. Eng."},{"key":"4960_CR52","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2013.2264721","author":"J Lee","year":"2013","unstructured":"Lee, J., Nam, Y., McManus, D.D., Chon, K.H.: Time-varying coherence function for atrial fibrillation detection. IEEE Trans. Biomed. Eng. (2013). https:\/\/doi.org\/10.1109\/TBME.2013.2264721","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"4960_CR53","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2015.2450773","author":"R Guti\u00e9rrez-Rivas","year":"2015","unstructured":"Guti\u00e9rrez-Rivas, R., Garcia, J.J., Marnane, W.P., Hern\u00e1ndez, A.: Novel real-time low-complexity QRS complex detector based on adaptive thresholding. IEEE Sens. J. (2015). https:\/\/doi.org\/10.1109\/JSEN.2015.2450773","journal-title":"IEEE Sens. J."},{"key":"4960_CR54","doi-asserted-by":"publisher","DOI":"10.1109\/CIC.2003.1291223","author":"HC Chen","year":"2003","unstructured":"Chen, H.C., Chen, S.W.: A moving average based filtering system with its application to real-time QRS detection. Comput. Cardiol. (2003). https:\/\/doi.org\/10.1109\/CIC.2003.1291223","journal-title":"Comput. Cardiol."},{"key":"4960_CR55","doi-asserted-by":"publisher","DOI":"10.1007\/BF02478504","author":"NV Thakor","year":"1983","unstructured":"Thakor, N.V., Webster, J.G., Tompkins, W.J.: Optimal QRS detector. Med. Biol. Eng. Comput. (1983). https:\/\/doi.org\/10.1007\/BF02478504","journal-title":"Med. Biol. Eng. Comput."},{"key":"4960_CR56","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2015.12.039","author":"JE Poole","year":"2016","unstructured":"Poole, J.E., Singh, J.P., Birgersdotter-Green, U.: QRS duration or QRS morphology: What really matters in cardiac resynchronization therapy? J. Am. Coll. Cardiol. (2016). https:\/\/doi.org\/10.1016\/j.jacc.2015.12.039","journal-title":"J. Am. Coll. Cardiol."},{"key":"4960_CR57","doi-asserted-by":"publisher","DOI":"10.1016\/j.gaceta.2021.10.052","author":"P Madona","year":"2021","unstructured":"Madona, P., Basti, R.I., Zain, M.M.: PQRST wave detection on ECG signals. Gac. (2021). https:\/\/doi.org\/10.1016\/j.gaceta.2021.10.052Sanit.","journal-title":"Gac"},{"key":"4960_CR58","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2010.04.012","author":"A Diery","year":"2011","unstructured":"Diery, A., Rowlands, D., Cutmore, T.R.H., James, D.: Automated ECG diagnostic P-wave analysis using wavelets. Comput. Methods Programs Biomed. (2011). https:\/\/doi.org\/10.1016\/j.cmpb.2010.04.012","journal-title":"Comput. Methods Programs Biomed."},{"issue":"200","key":"4960_CR59","doi-asserted-by":"publisher","first-page":"675","DOI":"10.2307\/2279372","volume":"32","author":"M Friedman","year":"1937","unstructured":"Friedman, M.: The use of ranks to avoid the assumption of normality implicit in the analysis of variance. J. Am. Stat. Assoc. 32(200), 675\u2013701 (1937). https:\/\/doi.org\/10.2307\/2279372","journal-title":"J. Am. Stat. Assoc."},{"key":"4960_CR60","first-page":"1","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar, J.: Statistical comparisons of classifiers over multiple data sets. J. Mach. Learn. Res. 7, 1\u201330 (2006)","journal-title":"J. Mach. Learn. Res."},{"key":"4960_CR61","unstructured":"Nemenyi, P.: Distribution-free multiple comparisons. Ph.D. thesis, Princeton University (1963)"},{"key":"4960_CR62","unstructured":"Molnar, C.: Interpretable machine learning: A guide for making black box models explainable. (2025)"},{"key":"4960_CR63","unstructured":"Lundberg, S.M., Lee, S.I.: A unified approach to interpreting model predictions(NeurIPS) (2017)"},{"key":"4960_CR64","doi-asserted-by":"publisher","first-page":"657304","DOI":"10.3389\/fphys.2021.657304","volume":"12","author":"R Rouhi","year":"2021","unstructured":"Rouhi, R., Clausel, M., Oster, J., Lauer, F.: An interpretable hand-crafted feature-based model for atrial fibrillation detection. Front. Physiol. 12, 657304 (2021). https:\/\/doi.org\/10.3389\/fphys.2021.657304","journal-title":"Front. Physiol."},{"key":"4960_CR65","doi-asserted-by":"publisher","first-page":"107358","DOI":"10.1016\/j.compbiomed.2024.107358","volume":"164","author":"S Farrokhi","year":"2025","unstructured":"Farrokhi, S., Ghasemzadeh, H., Kiani, M.: Reliable peak detection and feature extraction for wireless electrocardiograms. Comput. Biol. Med. 164, 107358 (2025). https:\/\/doi.org\/10.1016\/j.compbiomed.2024.107358","journal-title":"Comput. Biol. Med."},{"issue":"3","key":"4960_CR66","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1159\/000522508","volume":"147","author":"T Kabutoya","year":"2022","unstructured":"Kabutoya, T., Hoshide, S., Kario, K.: Notched P-wave on digital electrocardiogram predicts cardiovascular events in patients with cardiovascular risks: The Japan morning surge home blood pressure (J-HOP) study. Cardiology. 147(3), 307\u2013314 (2022). https:\/\/doi.org\/10.1159\/000522508","journal-title":"Cardiology"},{"issue":"1","key":"4960_CR67","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.hrthm.2010.09.020","volume":"8","author":"JW Magnani","year":"2011","unstructured":"Magnani, J.W., Gorodeski, E.Z., Johnson, V.M., Sullivan, L.M., Hamburg, N.M., Benjamin, E.J., Ellinor, P.T.: P wave duration is associated with cardiovascular and all-cause mortality outcomes: The National Health and Nutrition Examination Survey. Heart Rhythm. 8(1), 93\u2013100 (2011). https:\/\/doi.org\/10.1016\/j.hrthm.2010.09.020","journal-title":"Heart Rhythm"},{"key":"4960_CR68","doi-asserted-by":"publisher","first-page":"148","DOI":"10.3389\/fphys.2012.00148","volume":"3","author":"MA Peltola","year":"2012","unstructured":"Peltola, M.A.: Role of editing of R\u2013R intervals in the analysis of heart rate variability. Front. Physiol. 3, 148 (2012). https:\/\/doi.org\/10.3389\/fphys.2012.00148","journal-title":"Front. Physiol."},{"key":"4960_CR69","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2019.06.024","author":"Q Yao","year":"2020","unstructured":"Yao, Q., Wang, R., Fan, X., Liu, J., Li, Y.: Multi-class arrhythmia detection from 12-Lead varied-length ECG using attention-based time-incremental convolutional neural network. Inf. Fusion. (2020). https:\/\/doi.org\/10.1016\/j.inffus.2019.06.024","journal-title":"Inf. Fusion"},{"key":"4960_CR70","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-021-92172-5","author":"YS Baek","year":"2021","unstructured":"Baek, Y.S., Lee, S.C., Choi, W., Kim, D.H.: A new deep learning algorithm of 12-Lead electrocardiogram for identifying atrial fibrillation during sinus rhythm. Sci. Rep. (2021). https:\/\/doi.org\/10.1038\/s41598-021-92172-5","journal-title":"Sci. Rep."},{"key":"4960_CR71","doi-asserted-by":"publisher","DOI":"10.1016\/j.cjca.2020.02.096","author":"KC Chang","year":"2021","unstructured":"Chang, K.C., Hsieh, P.H., Wu, M.Y.: Usefulness of machine learning-based detection and classification of cardiac arrhythmias with 12-Lead electrocardiograms. Can. J. Cardiol. (2021). https:\/\/doi.org\/10.1016\/j.cjca.2020.02.096","journal-title":"Can. J. Cardiol."},{"key":"4960_CR72","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2017.2756869","author":"T Yang","year":"2018","unstructured":"Yang, T., Yu, L., Jin, Q., Wu, L., He, B.: Localization of origins of premature ventricular contraction by means of convolutional neural network from 12-Lead ECG. IEEE Trans. Biomed. Eng. (2018). https:\/\/doi.org\/10.1109\/TBME.2017.2756869","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"4960_CR73","doi-asserted-by":"publisher","DOI":"10.2196\/47803","author":"BBS Chuang","year":"2024","unstructured":"Chuang, B.B.S., Yang, A.C.: Optimization of using multiple machine learning approaches in atrial fibrillation detection based on a large-scale data set of 12-Lead electrocardiograms: Cross-sectional study. JMIR Form. Res. (2024). https:\/\/doi.org\/10.2196\/47803","journal-title":"JMIR Form. Res."}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04960-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-025-04960-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04960-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T00:55:24Z","timestamp":1764723324000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-025-04960-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,17]]},"references-count":73,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["4960"],"URL":"https:\/\/doi.org\/10.1007\/s11760-025-04960-5","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"type":"print","value":"1863-1703"},{"type":"electronic","value":"1863-1711"}],"subject":[],"published":{"date-parts":[[2025,11,17]]},"assertion":[{"value":"16 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 October 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 November 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 November 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"We declare that this manuscript is original has not been published before and is not currently being considered for publication elsewhere.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"1367"}}