{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T16:39:06Z","timestamp":1778603946962,"version":"3.51.4"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"15","license":[{"start":{"date-parts":[[2023,10,19]],"date-time":"2023-10-19T00:00:00Z","timestamp":1697673600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,10,19]],"date-time":"2023-10-19T00:00:00Z","timestamp":1697673600000},"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":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-17095-x","type":"journal-article","created":{"date-parts":[[2023,10,19]],"date-time":"2023-10-19T06:01:48Z","timestamp":1697695308000},"page":"45989-46016","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["ECG signal classification using DEA with LSTM for arrhythmia detection"],"prefix":"10.1007","volume":"83","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6088-6806","authenticated-orcid":false,"given":"Sumanta","family":"Kuila","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Namrata","family":"Dhanda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Subhankar","family":"Joardar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,10,19]]},"reference":[{"issue":"1","key":"17095_CR1","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/10.362922","volume":"42","author":"C Li","year":"1995","unstructured":"Li C, Zheng C, Tai C (1995) Detection of ECG characteristic poin ts using wavelet transforms. IEEE Trans Biomed Eng 42(1):21\u201328","journal-title":"IEEE Trans Biomed Eng"},{"key":"17095_CR2","doi-asserted-by":"publisher","unstructured":"Patro KK, Kumar PR (2017) Machine learning classification approaches for biometric recognition system using ECG signals. J Eng Sci Technol Rev 1\u20138. https:\/\/doi.org\/10.25103\/jestr.106.01","DOI":"10.25103\/jestr.106.01"},{"key":"17095_CR3","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1016\/j.dsp.2005.12.003","volume":"16","author":"BN Singh","year":"2006","unstructured":"Singh BN, Tiwari AK (2006) Optimal selection of wavelet basis function applied to ECG signal denoising. Dig Sign Proc 16:275\u2013287","journal-title":"Dig Sign Proc"},{"key":"17095_CR4","doi-asserted-by":"publisher","unstructured":"Huanhuan M, Yue Z ( 2014) Classification of electrocardiogram signals with deep belief networks. IEEE 17th Int Conf Comput Sci Eng.\u00a0https:\/\/doi.org\/10.1109\/CSE.2014.36","DOI":"10.1109\/CSE.2014.36"},{"issue":"11","key":"17095_CR5","doi-asserted-by":"publisher","first-page":"2758","DOI":"10.1109\/78.650102","volume":"45","author":"B Scholkopf","year":"1997","unstructured":"Scholkopf B, Sung KK, Burges CJC, GirosiF NFP, Poggio T, Vapnik V (1997) Comparing support vector machines with Gaussian kernels to radial basis function classifiers. IEEE Trans Signal Process 45(11):2758\u20132765","journal-title":"IEEE Trans Signal Process"},{"issue":"9","key":"17095_CR6","doi-asserted-by":"publisher","first-page":"826","DOI":"10.1109\/10.58593","volume":"37","author":"DA Coast","year":"1990","unstructured":"Coast DA, Stern RM, Cano GG, Briller SA (1990) An approach to cardiac arrhythmia analysis using hidden Markov models. IEEE Trans Biomed Eng 37(9):826\u2013836","journal-title":"IEEE Trans Biomed Eng"},{"key":"17095_CR7","unstructured":"Prasad GK, Sahambi JS (2003) Classification of ECG arrhythmias using multi-resolution analysis and neural networks. Conference Proceedings. IEEE Convergent Tech, pp.227\u2013231."},{"key":"17095_CR8","doi-asserted-by":"publisher","unstructured":"Yu SN, Chou KT (2006) Combining independent component analysis and backpropagation neural network for ECG beat classification. Conference proceedings. IEEE Eng Med Biol Soc,\u00a0New York, pp. 3090\u20133093. https:\/\/doi.org\/10.1109\/IEMBS.2006.260290","DOI":"10.1109\/IEMBS.2006.260290"},{"key":"17095_CR9","doi-asserted-by":"publisher","first-page":"25627","DOI":"10.1109\/ACCESS.2018.2877793","volume":"7","author":"W Li","year":"2019","unstructured":"Li W (2019) Wavelets for electrocardiogram: overview and taxonomy. IEEE Access 7:25627\u201325649","journal-title":"IEEE Access"},{"issue":"6","key":"17095_CR10","doi-asserted-by":"publisher","first-page":"6598","DOI":"10.11591\/ijece.v10i6.pp6598-6605","volume":"10","author":"S Kuila","year":"2020","unstructured":"Kuila S, Dhanda N, Joardar S (2020) Feature extraction of electrocardiogram signal using machine learning classification. Int J Electr Comput Eng (IJECE) 10(6):6598\u20136605","journal-title":"Int J Electr Comput Eng (IJECE)"},{"key":"17095_CR11","doi-asserted-by":"publisher","first-page":"105607","DOI":"10.1016\/j.cmpb.2020.105607","volume":"196","author":"DK Atal","year":"2020","unstructured":"Atal DK, Singh M (2020) Arrhythmia classification with ECG signals based on the optimization-enabled deep convolutional neural network. Comput Methods Programs Biomed 196:105607","journal-title":"Comput Methods Programs Biomed"},{"key":"17095_CR12","doi-asserted-by":"publisher","unstructured":"Li Q, Cai W, Wang X, Zhou Y, Feng DD, Chen M (2014) Medical image classification with convolutional neural network. 13th International Conference on Control Automation Robotics & Vision (ICARCV) .Singapore: IEEE. 844\u2013848. https:\/\/doi.org\/10.1109\/ICARCV.2014.7064414","DOI":"10.1109\/ICARCV.2014.7064414"},{"issue":"3","key":"17095_CR13","doi-asserted-by":"publisher","first-page":"664","DOI":"10.1109\/TBME.2015.2468589","volume":"63","author":"S Kiranyaz","year":"2016","unstructured":"Kiranyaz S, Ince T, Gabbouj M (2016) Real-time patient-specific ECG classification by 1-D convolutional neural networks. IEEE Trans Biomed Eng 63(3):664\u2013675","journal-title":"IEEE Trans Biomed Eng"},{"key":"17095_CR14","doi-asserted-by":"crossref","unstructured":"Kachuee M, Fazeli S (2018) Ecg heartbeat classification: a deep transferable representation. IEEE International Conference on Healthcare Informatics, pp. 443\u2013444.","DOI":"10.1109\/ICHI.2018.00092"},{"issue":"8","key":"17095_CR15","doi-asserted-by":"publisher","first-page":"2168","DOI":"10.1109\/TBME.2011.2113395","volume":"58","author":"T Mar","year":"2011","unstructured":"Mar T, Zaunseder S, Martinez JP, Llamedo M, Poll R (2011) Optimization of ECG classification by means of feature selection. IEEE Trans Biomed Eng 58(8):2168\u20132177","journal-title":"IEEE Trans Biomed Eng"},{"issue":"2","key":"17095_CR16","first-page":"14","volume":"10","author":"S Nurmaini","year":"2018","unstructured":"Nurmaini S, Radiyati Umi P, Muhammad Naufal R, Gani A (2018) Cardiac arrhythmias classification using deep neural networks and principal component analysis algorithm. Int J Adv Soft Comput Appl 10(2):14\u201332","journal-title":"Int J Adv Soft Comput Appl"},{"key":"17095_CR17","unstructured":"Rajpurkar P, Hannun AY, Haghpanahi M, Bourn C, Andrew Y. Ng. (2017) Cardiologist-level arrhythmia detection with convolutional neural networks. arXiv preprint arXiv: 1707.01836v1."},{"key":"17095_CR18","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/j.compbiomed.2018.12.012","volume":"105","author":"SL Oh","year":"2019","unstructured":"Oh SL, Ng EYK, Tan RS, Acharya UR (2019) Automated beat-wise arrhythmia diagnosis using modified U-net on extended electrocardiographic recordings with heterogeneous arrhythmia types. Comput Biol Med 105:92\u2013101. https:\/\/doi.org\/10.1016\/j.compbiomed.2018.12.012","journal-title":"Comput Biol Med"},{"issue":"18","key":"17095_CR19","doi-asserted-by":"publisher","first-page":"25233","DOI":"10.1007\/s11042-022-11957-6","volume":"81","author":"S Kuila","year":"2021","unstructured":"Kuila S, Dhanda N, Joardar S (2021) ECG signal classification and arrhythmia detection using ELM-RNN. Multimedia Tools Appl 81(18):25233\u201325249 (Springer Nature)","journal-title":"Multimedia Tools Appl"},{"key":"17095_CR20","first-page":"404","volume":"8","author":"A Sherstinsky","year":"2020","unstructured":"Sherstinsky A (2020) Fundamentals of recurrent neural network (RNN) and long short-term memory (LSTM) network. Physica D 8:404","journal-title":"Physica D"},{"key":"17095_CR21","doi-asserted-by":"crossref","unstructured":"Kuila S, Dhanda N, Joardar S (2019) Feature extraction and classification of MIT-BIH arrhythmia database. 2nd International Conference on Communication, Devices and Computing, Haldia Institute of Technology. Springer proceeding (LNEE) 602: 417\u2013427.","DOI":"10.1007\/978-981-15-0829-5_41"},{"issue":"3","key":"17095_CR22","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1109\/51.932724","volume":"20","author":"GB Moody","year":"2001","unstructured":"Moody GB, Mark RG (2001) The impact of the MIT-BIH arrhythmia database. IEEE Eng Med Biol Mag 20(3):45\u201350","journal-title":"IEEE Eng Med Biol Mag"},{"key":"17095_CR23","doi-asserted-by":"publisher","first-page":"2222","DOI":"10.1109\/TNNLS.2016.2582924","volume":"28","author":"K Greff","year":"2016","unstructured":"Greff K, Srivastava RK, Koutnik J, Steunebrink BR, Schmidhuber J (2016) LSTM: a search space odyssey. IEEE Trans Neural Netw Learn Syst 28:2222\u20132232. https:\/\/doi.org\/10.1109\/TNNLS.2016.2582924","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"17095_CR24","doi-asserted-by":"publisher","first-page":"1750","DOI":"10.1109\/TNN.2007.900239","volume":"18","author":"W Jiang","year":"2007","unstructured":"Jiang W, Kong SG (2007) Block-based neural networks for personalized ECG signal classification. IEEE Trans Neural Netw 18:1750\u20131761. https:\/\/doi.org\/10.1109\/TNN.2007.900239","journal-title":"IEEE Trans Neural Netw"},{"issue":"6","key":"17095_CR25","doi-asserted-by":"publisher","first-page":"1411","DOI":"10.1109\/TNN.2006.880583","volume":"17","author":"NY Liang","year":"2006","unstructured":"Liang NY, Huang GB, Saratchandran P, Sundararajan N (2006) A fast and accurate online sequential learning algorithm for feedforward networks. IEEE Trans Neural Networks 17(6):1411\u20131423","journal-title":"IEEE Trans Neural Networks"},{"key":"17095_CR26","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1016\/j.compbiomed.2018.09.009","volume":"102","author":"O Y\u0131ld\u0131r\u0131m","year":"2018","unstructured":"Y\u0131ld\u0131r\u0131m O, Plawiak P, Tan RS, Acharya UR (2018) Arrhythmia detection using deep convolutional neural network with long duration ECG signals. Comput Biol Med 102:411\u2013420","journal-title":"Comput Biol Med"},{"issue":"14","key":"17095_CR27","first-page":"1817","volume":"99","author":"S Kuila","year":"2021","unstructured":"Kuila S, Dhanda N, Joardar S (2021) ECG signal classification for arrhythmia detection using DEA and ELM. J Theor Appl Inf Technol 99(14):1817\u20133195","journal-title":"J Theor Appl Inf Technol"},{"key":"17095_CR28","doi-asserted-by":"publisher","first-page":"109515","DOI":"10.1016\/j.mehy.2019.109515","volume":"136","author":"A Dikera","year":"2020","unstructured":"Dikera A, Avcib E, Tanyildizib E (2020) Gedikpinarc M (2020) A novel ECG signal classification method using DEA-ELM. Medical Hypotheses 136:109515 (Elsevier)","journal-title":"Medical Hypotheses"},{"key":"17095_CR29","doi-asserted-by":"publisher","first-page":"2181","DOI":"10.1016\/j.procs.2020.03.269","volume":"167","author":"SK Pandey","year":"2020","unstructured":"Pandey SK, Janghel RP, Vani V (2020) Patient specific machine learning models for ECG signal classification. Procedia Comput Sci 167:2181\u20132190. https:\/\/doi.org\/10.1016\/j.procs.2020.03.269","journal-title":"Procedia Comput Sci"},{"issue":"1","key":"17095_CR30","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1109\/JETCAS.2013.2242772","volume":"3","author":"T Chen","year":"2013","unstructured":"Chen T, Mazomenos EB, Maharatna K (2013) Design of a low-power on-body ECG classifier for remote cardiovascular monitoring systems. IEEE J Emerg Sel Top Circ Syst 3(1):75\u201385","journal-title":"IEEE J Emerg Sel Top Circ Syst"},{"key":"17095_CR31","doi-asserted-by":"publisher","first-page":"582","DOI":"10.1109\/TBME.2004.824138","volume":"51","author":"S Osowski","year":"2004","unstructured":"Osowski S, Hoai LT, Markiewicz T (2004) Support vector machine based expert system for reliable heartbeat recognition. IEEE Trans Biomed Engine 51:582\u2013589","journal-title":"IEEE Trans Biomed Engine"},{"key":"17095_CR32","doi-asserted-by":"crossref","unstructured":"Anwar SM, Gul M, Majid M, Majdi A (2018) Arrhythmia classification of ECG signals using hybrid features. Hindawi, Computational and Mathematical Methods in Medicine. Article ID 1380348.","DOI":"10.1155\/2018\/1380348"},{"key":"17095_CR33","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1109\/JBHI.2019.2911367","volume":"24","author":"S Saadatnejad","year":"2019","unstructured":"Saadatnejad S, Oveisi M, Hashemi M (2019) LSTM-based ECG classification for continuous monitoring on personal wearable devices. IEEE J Biomed Health Inform 24:515\u2013523","journal-title":"IEEE J Biomed Health Inform"},{"issue":"1","key":"17095_CR34","first-page":"205","volume":"4","author":"SM Jadhav","year":"2011","unstructured":"Jadhav SM, Nalbalwar SL, Ghatol AA (2011) Modular neural network based arrhythmia classification system using ECG signal Data. Int J Inf Technol Knowl Manag 4(1):205\u2013209","journal-title":"Int J Inf Technol Knowl Manag"},{"key":"17095_CR35","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1016\/j.eswa.2018.08.011","volume":"115","author":"RS Andersen","year":"2019","unstructured":"Andersen RS, Peimankar A (2019) A deep learning approach for real-time detection of atrial fibrillation. Expert Syst Appl 115:465\u2013473","journal-title":"Expert Syst Appl"},{"issue":"6","key":"17095_CR36","doi-asserted-by":"publisher","first-page":"1744","DOI":"10.1109\/JBHI.2018.2858789","volume":"22","author":"X Fan","year":"2018","unstructured":"Fan X, Yao Q, Cai Y, Miao F, Sun F (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":"7","key":"17095_CR37","doi-asserted-by":"publisher","first-page":"2047","DOI":"10.1007\/s00521-018-3616-9","volume":"30","author":"M Amrani","year":"2018","unstructured":"Amrani M, Hammad M, Jiang F, Wang K, Amrani A (2018) Very deep feature extraction and fusion for arrhythmias detection. Neural Comput Appl 30(7):2047\u20132057.\u00a0 https:\/\/doi.org\/10.1007\/s00521-018-3616-9","journal-title":"Neural Comput Appl"},{"key":"17095_CR38","unstructured":"https:\/\/physionet.org\/content\/mitdb\/1.0.0\/"},{"issue":"6","key":"17095_CR39","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1109\/TBME.2015.2468589","volume":"63","author":"S Kiranyaz","year":"2016","unstructured":"Kiranyaz S, Ince T, Gabbouj M (2016) Real-time patient-specific ECG classification by 1-D convolutional neural networks. IEEE Trans Biomed Eng 63(6):664\u2013675. https:\/\/doi.org\/10.1109\/TBME.2015.2468589","journal-title":"IEEE Trans Biomed Eng"},{"key":"17095_CR40","doi-asserted-by":"crossref","unstructured":"Martis RJ, Acharya UR, Lim CM, Mandana K, Ray AK, Chakraborty C (2013) Application of higher order cumulant features for cardiac health diagnosis using ECG signals. Int J Neural Syst","DOI":"10.1142\/S0129065713500147"},{"issue":"7","key":"17095_CR41","first-page":"18","volume":"6","author":"V Srivastava","year":"2021","unstructured":"Srivastava V, Gupta S, Chaudhary G, Balodi A, Khari M, Garc\u00eda-D\u00edaz V (2021) An enhanced texture-based feature extraction approach for classification of biomedical images of CT-scan of lungs. Int J Interact Multimedia Artif Intell 6(7):18\u201325","journal-title":"Int J Interact Multimedia Artif Intell"},{"issue":"4","key":"17095_CR42","first-page":"69","volume":"7","author":"A Laishram","year":"2022","unstructured":"Laishram A, Thongam K (2022) Automatic classification of oral pathologies using orthopantomogram radiography images based on convolutional neural network. Int J Interact Multimedia Artif Intell 7(4):69\u201377","journal-title":"Int J Interact Multimedia Artif Intell"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17095-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-17095-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17095-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T11:35:30Z","timestamp":1714390530000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-17095-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,19]]},"references-count":42,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["17095"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-17095-x","relation":{},"ISSN":["1573-7721"],"issn-type":[{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,19]]},"assertion":[{"value":"19 March 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 June 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 September 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 October 2023","order":4,"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 there is no conflict of interest in this research.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}