{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T23:28:51Z","timestamp":1747265331095,"version":"3.37.3"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"22","license":[{"start":{"date-parts":[[2021,6,6]],"date-time":"2021-06-06T00:00:00Z","timestamp":1622937600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,6,6]],"date-time":"2021-06-06T00:00:00Z","timestamp":1622937600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62073086","61973087","U1911401"],"award-info":[{"award-number":["62073086","61973087","U1911401"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2021,11]]},"DOI":"10.1007\/s00521-021-06148-7","type":"journal-article","created":{"date-parts":[[2021,6,6]],"date-time":"2021-06-06T07:02:21Z","timestamp":1622962941000},"page":"15281-15292","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Dual temporal convolutional network for single-lead fibrillation waveform extraction"],"prefix":"10.1007","volume":"33","author":[{"given":"Jun","family":"Lu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhuoyan","family":"Xie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kan","family":"Xie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanxiong","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shengli","family":"Xie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,6,6]]},"reference":[{"issue":"1","key":"6148_CR1","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/j.gheart.2014.01.004","volume":"9","author":"SS Chugh","year":"2014","unstructured":"Chugh SS, Roth GA, Gillum RF, Mensah GA (2014) Global burden of atrial fibrillation in developed and developing nations. Glob Heart 9(1):113\u2013119","journal-title":"Glob Heart"},{"issue":"2","key":"6148_CR2","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1016\/S0735-1097(00)01107-4","volume":"37","author":"SS Chugh","year":"2001","unstructured":"Chugh SS, Blackshear JL, Win-Kuang S, Hammill SC, Gersh BJ (2001) Epidemiology and natural history of atrial fibrillation: clinical implications. J Am Coll Cardiol 37(2):371\u2013378","journal-title":"J Am Coll Cardiol"},{"issue":"4","key":"6148_CR3","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1016\/j.amjcard.2004.10.025","volume":"95","author":"H Daniela","year":"2005","unstructured":"Daniela H, Martin S, Leif S, Christoph G, Klein HU, Bertil OS, Andreas B (2005) Time-frequency analysis of the surface electrocardiogram for monitoring antiarrhythmic drug effects in atrial fibrillation. Am J Cardiol 95(4):526\u2013528","journal-title":"Am J Cardiol"},{"issue":"6","key":"6148_CR4","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1111\/jce.12645","volume":"26","author":"VP Raygor","year":"2015","unstructured":"Raygor VP, Jason N, Goldberger JJ (2015) Surface ECG f wave analysis of dofetilide drug effect in the atrium. J Cardiovasc Electrophysiol 26(6):644\u2013648","journal-title":"J Cardiovasc Electrophysiol"},{"issue":"2","key":"6148_CR5","doi-asserted-by":"publisher","first-page":"e003354","DOI":"10.1161\/CIRCEP.115.003354","volume":"9","author":"T Lankveld","year":"2016","unstructured":"Lankveld T, Zeemering S, Scherr D, Kuklik P, Hoffmann BA, Willems S, Pieske B, Ha\u00efssaguerre M, Ja\u00efs P, Crijns HJ et al (2016) Atrial fibrillation complexity parameters derived from surface ECGs predict procedural outcome and long-term follow-up of stepwise catheter ablation for atrial fibrillation. Circ Arrhythm Electrophysiol 9(2):e003354","journal-title":"Circ Arrhythm Electrophysiol"},{"issue":"11","key":"6148_CR6","doi-asserted-by":"publisher","first-page":"3307","DOI":"10.1007\/s10439-016-1641-3","volume":"44","author":"A Ra\u00fal","year":"2016","unstructured":"Ra\u00fal A, Fernando H, Rieta JJ (2016) Electrocardiographic spectral features for long-term outcome prognosis of atrial fibrillation catheter ablation. Ann Biomed Eng 44(11):3307\u20133318","journal-title":"Ann Biomed Eng"},{"issue":"6","key":"6148_CR7","first-page":"1573","volume":"21","author":"RE Kheirati","year":"2016","unstructured":"Kheirati RE, Roberto S (2016) An extended Bayesian framework for atrial and ventricular activity separation in atrial fibrillation. IEEE J Biomed Health Inform 21(6):1573\u20131580","journal-title":"IEEE J Biomed Health Inform"},{"issue":"7","key":"6148_CR8","doi-asserted-by":"publisher","first-page":"1176","DOI":"10.1109\/TBME.2004.827272","volume":"51","author":"RJ Joaqu\u00edn","year":"2004","unstructured":"Joaqu\u00edn RJ, Francisco C, C\u00e9sar S, Vicente Z, Jos\u00e9 M (2004) Atrial activity extraction for atrial fibrillation analysis using blind source separation. IEEE Trans Biomed Eng 51(7):1176\u20131186","journal-title":"IEEE Trans Biomed Eng"},{"issue":"2","key":"6148_CR9","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1109\/TBME.2004.840473","volume":"52","author":"C Francisco","year":"2005","unstructured":"Francisco C, Joaqu\u00edn RJ, Jos\u00e9 M, Vicente Z (2005) Spatiotemporal blind source separation approach to atrial activity estimation in atrial tachyarrhythmias. IEEE Trans Biomed Eng 52(2):258\u2013267","journal-title":"IEEE Trans Biomed Eng"},{"issue":"8","key":"6148_CR10","doi-asserted-by":"publisher","first-page":"1530","DOI":"10.1109\/TBME.2006.889778","volume":"54","author":"V Carlos","year":"2007","unstructured":"Carlos V, Rieta Jos\u00e9 J, C\u00e9sar S, David M (2007) Convolutive blind source separation algorithms applied to the electrocardiogram of atrial fibrillation: study of performance. IEEE Trans Biomed Eng 54(8):1530\u20131533","journal-title":"IEEE Trans Biomed Eng"},{"issue":"2","key":"6148_CR11","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/j.artmed.2009.05.006","volume":"47","author":"L Raul","year":"2009","unstructured":"Raul L, Jorge I (2009) Application of constrained independent component analysis algorithms in electrocardiogram arrhythmias. Artif Intell Med 47(2):121\u2013133","journal-title":"Artif Intell Med"},{"issue":"1","key":"6148_CR12","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1109\/10.900266","volume":"48","author":"S Martin","year":"2001","unstructured":"Martin S, Sornmo L (2001) Spatiotemporal QRST cancellation techniques for analysis of atrial fibrillation. IEEE Trans Biomed Eng 48(1):105\u2013111","journal-title":"IEEE Trans Biomed Eng"},{"key":"6148_CR13","doi-asserted-by":"crossref","unstructured":"Lemay M, Jacquemet V, Forclaz A, Vesin JM, Kappenberger L (2005) Spatiotemporal QRST cancellation method using separate QRS and T-waves templates. In: Computers in cardiology, 2005. IEEE, pp 611\u2013614","DOI":"10.1109\/CIC.2005.1588175"},{"issue":"3","key":"6148_CR14","doi-asserted-by":"publisher","first-page":"542","DOI":"10.1109\/TBME.2006.888835","volume":"54","author":"L Mathieu","year":"2007","unstructured":"Mathieu L, Jean-Marc V, Adriaan VO, Vincent J, Lukas K (2007) Cancellation of ventricular activity in the ECG: evaluation of novel and existing methods. IEEE Trans Biomed Eng 54(3):542\u2013546","journal-title":"IEEE Trans Biomed Eng"},{"issue":"3","key":"6148_CR15","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1016\/j.compbiomed.2012.12.005","volume":"43","author":"D Huhe","year":"2013","unstructured":"Huhe D, Shouda J, Ye L (2013) Atrial activity extraction from single lead ECG recordings: evaluation of two novel methods. Comput Biol Med 43(3):176\u2013183","journal-title":"Comput Biol Med"},{"issue":"7","key":"6148_CR16","doi-asserted-by":"publisher","first-page":"1310","DOI":"10.1088\/1361-6579\/aa707c","volume":"38","author":"M John","year":"2017","unstructured":"John M, Neil R, Chun-Li W, Hau-tieng W (2017) Single-lead f-wave extraction using diffusion geometry. Physiol Meas 38(7):1310","journal-title":"Physiol Meas"},{"key":"6148_CR17","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1146\/annurev-bioeng-071516-044442","volume":"19","author":"S Dinggang","year":"2017","unstructured":"Dinggang S, Guorong W, Heung-Il S (2017) Deep learning in medical image analysis. Annu Rev Biomed Eng 19:221\u2013248","journal-title":"Annu Rev Biomed Eng"},{"key":"6148_CR18","doi-asserted-by":"publisher","first-page":"113693","DOI":"10.1016\/j.eswa.2020.113693","volume":"161","author":"\u00d6 \u015eaban","year":"2020","unstructured":"\u015eaban \u00d6 (2020) Stacked auto-encoder based tagging with deep features for content-based medical image retrieval. Expert Syst Appl 161:113693","journal-title":"Expert Syst Appl"},{"key":"6148_CR19","first-page":"100033","volume":"X","author":"Z Ebrahimi","year":"2020","unstructured":"Ebrahimi Z, Loni M, Daneshtalab M, Gharehbaghi A (2020) A review on deep learning methods for ECG arrhythmia classification. Expert Syst Appl X:100033","journal-title":"Expert Syst Appl"},{"issue":"3","key":"6148_CR20","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1002\/ima.22309","volume":"29","author":"\u00d6 \u015eaban","year":"2019","unstructured":"\u015eaban \u00d6, Bayram A (2019) Cell-type based semantic segmentation of histopathological images using deep convolutional neural networks. Int J Imaging Syst Technol 29(3):234\u2013246","journal-title":"Int J Imaging Syst Technol"},{"issue":"12","key":"6148_CR21","doi-asserted-by":"publisher","first-page":"2095","DOI":"10.1109\/TSMC.2017.2705582","volume":"48","author":"P Bahareh","year":"2018","unstructured":"Bahareh P, Javan RM, Khashayar K (2018) Deep convolutional neural networks and learning ECG features for screening paroxysmal atrial fibrillation patients. IEEE Trans Syst Man Cybern Syst 48(12):2095\u20132104","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"issue":"6","key":"6148_CR22","doi-asserted-by":"publisher","first-page":"1744","DOI":"10.1109\/JBHI.2018.2858789","volume":"22","author":"F Xiaomao","year":"2018","unstructured":"Xiaomao F, Qihang Y, Yunpeng C, Fen M, Fangmin S, Ye L (2018) Multiscaled fusion of deep convolutional neural networks for screening atrial fibrillation from single lead short ECG recordings. IEEE J Biomed Health Inform 22(6):1744\u20131753","journal-title":"IEEE J Biomed Health Inform"},{"issue":"2","key":"6148_CR23","first-page":"515","volume":"24","author":"S Saeed","year":"2019","unstructured":"Saeed S, Mohammadhosein O, Matin H (2019) LSTM-based ECG classification for continuous monitoring on personal wearable devices. IEEE J Biomed Health Inform 24(2):515\u2013523","journal-title":"IEEE J Biomed Health Inform"},{"issue":"8","key":"6148_CR24","doi-asserted-by":"publisher","first-page":"1256","DOI":"10.1109\/TASLP.2019.2915167","volume":"27","author":"L Yi","year":"2019","unstructured":"Yi L, Nima M (2019) Conv-TasNet: surpassing ideal time-frequency magnitude masking for speech separation. IEEE\/ACM Trans Audio Speech Lang Process 27(8):1256\u20131266","journal-title":"IEEE\/ACM Trans Audio Speech Lang Process"},{"key":"6148_CR25","doi-asserted-by":"crossref","unstructured":"Luo Y, Mesgarani N (2018) TasNet: time-domain audio separation network for real-time, single-channel speech separation. In: 2018 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 696\u2013700","DOI":"10.1109\/ICASSP.2018.8462116"},{"key":"6148_CR26","doi-asserted-by":"crossref","unstructured":"Pandey A, Wang D (2019) TCNN: temporal convolutional neural network for real-time speech enhancement in the time domain. In: ICASSP 2019\u20132019 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 6875\u20136879","DOI":"10.1109\/ICASSP.2019.8683634"},{"key":"6148_CR27","doi-asserted-by":"crossref","unstructured":"Yu D, Kolb\u00e6k M, Tan Z-H, Jensen J (2017) Permutation invariant training of deep models for speaker-independent multi-talker speech separation. In: 2017 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 241\u2013245","DOI":"10.1109\/ICASSP.2017.7952154"},{"key":"6148_CR28","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.compeleceng.2018.03.025","volume":"67","author":"\u00d6 \u015eaban","year":"2018","unstructured":"\u015eaban \u00d6, Bayram A (2018) Phase classification of mitotic events using selective dictionary learning for stem cell populations. Comput Electr Eng 67:25\u201337","journal-title":"Comput Electr Eng"},{"key":"6148_CR29","unstructured":"Bai S, Kolter JZ, Koltun V (2018) An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271"},{"issue":"4","key":"6148_CR30","doi-asserted-by":"publisher","first-page":"680","DOI":"10.1016\/j.camwa.2007.04.035","volume":"55","author":"L Chia-Hung","year":"2008","unstructured":"Chia-Hung L (2008) Frequency-domain features for ECG beat discrimination using grey relational analysis-based classifier. Comput Math Appl 55(4):680\u2013690","journal-title":"Comput Math Appl"},{"key":"6148_CR31","unstructured":"Kingma DP, Ba J (2014) Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"issue":"7","key":"6148_CR32","doi-asserted-by":"publisher","first-page":"075011","DOI":"10.1088\/1361-6579\/ab2b17","volume":"40","author":"A Ra\u00fal","year":"2019","unstructured":"Ra\u00fal A, Leif S, Rieta JJ (2019) Reference database and performance evaluation of methods for extraction of atrial fibrillatory waves in the ECG. Physiol Meas 40(7):075011","journal-title":"Physiol Meas"},{"key":"6148_CR33","first-page":"043407","volume":"1","author":"S Reza","year":"2007","unstructured":"Reza S, Clifford GD, Jutten C, Shamsollahi MB (2007) Multichannel ECG and noise modeling: application to maternal and fetal ECG signals. EURASIP J Adv Signal Process 1:043407","journal-title":"EURASIP J Adv Signal Process"},{"issue":"11","key":"6148_CR34","doi-asserted-by":"publisher","first-page":"2058","DOI":"10.1088\/1361-6579\/aa9153","volume":"38","author":"P Andrius","year":"2017","unstructured":"Andrius P, Vaidotas M, Andrius S, Raimondas K, Jurgita S, Julien O, Leif S (2017) Electrocardiogram modeling during paroxysmal atrial fibrillation: application to the detection of brief episodes. Physiol Meas 38(11):2058","journal-title":"Physiol Meas"},{"issue":"s1","key":"6148_CR35","first-page":"317","volume":"40","author":"R Bousseljot","year":"1995","unstructured":"Bousseljot R, Kreiseler D, Schnabel A (1995) Nutzung der ekg-signaldatenbank cardiodat der ptb \u00fcber das internet. Biomed Eng 40(s1):317\u2013318","journal-title":"Biomed Eng"},{"key":"6148_CR36","first-page":"227","volume":"10","author":"G Moody","year":"1983","unstructured":"Moody G (1983) A new method for detecting atrial fibrillation using RR intervals. Comput Cardiol 10:227\u2013230","journal-title":"Comput Cardiol"},{"key":"6148_CR37","doi-asserted-by":"crossref","unstructured":"Clifford GD, Liu C, Moody B, Li-wei HL, Silva I, Li Q, Johnson AE, Mark RG (2017) AF classification from a short single lead ECG recording: the physionet\/computing in cardiology challenge 2017. In: 2017 computing in cardiology (CinC). IEEE, pp 1\u20134","DOI":"10.22489\/CinC.2017.065-469"},{"issue":"12","key":"6148_CR38","doi-asserted-by":"publisher","first-page":"1351","DOI":"10.1088\/0967-3334\/29\/12\/001","volume":"29","author":"A Ra\u00fal","year":"2008","unstructured":"Ra\u00fal A, Joaqu\u00edn RJ (2008) Adaptive singular value cancelation of ventricular activity in single-lead atrial fibrillation electrocardiograms. Physiol Meas 29(12):1351","journal-title":"Physiol Meas"},{"issue":"16","key":"6148_CR39","doi-asserted-by":"publisher","first-page":"4388","DOI":"10.1109\/TSP.2018.2853144","volume":"66","author":"GJJ Warmerdam","year":"2018","unstructured":"Warmerdam GJJ, Rik V, Lars S, Van Laar JOEH, Bergmans JWM (2018) Hierarchical probabilistic framework for fetal r-peak detection, using ECG waveform and heart rate information. IEEE Trans Signal Process 66(16):4388\u20134397","journal-title":"IEEE Trans Signal Process"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06148-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-021-06148-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06148-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,24]],"date-time":"2021-10-24T07:18:43Z","timestamp":1635059923000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-021-06148-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,6]]},"references-count":39,"journal-issue":{"issue":"22","published-print":{"date-parts":[[2021,11]]}},"alternative-id":["6148"],"URL":"https:\/\/doi.org\/10.1007\/s00521-021-06148-7","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2021,6,6]]},"assertion":[{"value":"29 January 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 May 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 June 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}