{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T10:38:31Z","timestamp":1788259111612,"version":"build-2803163510"},"reference-count":35,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Electrocardiology"],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1016\/j.jelectrocard.2025.154126","type":"journal-article","created":{"date-parts":[[2025,10,4]],"date-time":"2025-10-04T00:13:36Z","timestamp":1759536816000},"page":"154126","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":4,"special_numbering":"C","title":["An integrated fractional stockwell transform with atrous convolutions aided vision transformer based capsule network for fetal ECG arrhythmia detection"],"prefix":"10.1016","volume":"93","author":[{"given":"P","family":"Siva Priya","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"P","family":"Rajesh Kumar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G.","family":"Srinivas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Prasad Reddy","family":"PVGD","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.jelectrocard.2025.154126_bb0005","doi-asserted-by":"crossref","first-page":"951","DOI":"10.3390\/s21030951","article-title":"A hybrid deep CNN model for abnormal arrhythmia detection based on cardiac ECG signal","volume":"21","author":"Ullah","year":"2021","journal-title":"Sensors"},{"issue":"5","key":"10.1016\/j.jelectrocard.2025.154126_bb0010","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.ajog.2020.02.017","article-title":"Coronavirus disease 2019 (COVID-19) and pregnancy: what obstetricians need to know","volume":"222","author":"Rasmussen","year":"2020","journal-title":"Am J Obstet Gynecol"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0015","series-title":"Advanced methods in biomedical signal processing and analysis","first-page":"257","article-title":"New metrics to assess the subtle changes of the heart\u2019s electromagnetic field","author":"Chaikovsky","year":"2023"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0020","doi-asserted-by":"crossref","DOI":"10.3389\/fmed.2021.661226","article-title":"Non-linear methods predominant in fetal heart rate analysis: a systematic review","volume":"8","author":"Ribeiro","year":"2021","journal-title":"Front Med"},{"issue":"6","key":"10.1016\/j.jelectrocard.2025.154126_bb0025","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1080\/14767058.2021.1906220","article-title":"Does continuous cardiotocography during labor cause excessive fetal distress diagnosis and unnecessary cesarean sections?","volume":"35","author":"Kale","year":"2022","journal-title":"J Matern Fetal Neonatal Med"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0030","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12884-020-02918-8","article-title":"Feasibility of non-invasive foetal electrocardiography in a twin pregnancy","volume":"20","author":"Noben","year":"2020","journal-title":"BMC Pregnancy Childbirth"},{"issue":"7","key":"10.1016\/j.jelectrocard.2025.154126_bb0035","doi-asserted-by":"crossref","first-page":"475","DOI":"10.3390\/bios12070475","article-title":"Wearable fetal ECG monitoring system from abdominal electrocardiography recording","volume":"12","author":"Zhang","year":"2022","journal-title":"Biosensors"},{"issue":"2","key":"10.1016\/j.jelectrocard.2025.154126_bb0040","doi-asserted-by":"crossref","DOI":"10.1161\/JAHA.120.017839","article-title":"Changes in cardiomyocyte cell cycle and hypertrophic growth during fetal to adult in mammals","volume":"10","author":"Bishop","year":"2021","journal-title":"J Am Heart Assoc"},{"issue":"1","key":"10.1016\/j.jelectrocard.2025.154126_bb0045","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1152\/physrev.00036.2019","article-title":"Cardiac mechano-electric coupling: acute effects of mechanical stimulation on heart rate and rhythm","volume":"101","author":"Quinn","year":"2021","journal-title":"Physiol Rev"},{"issue":"18","key":"10.1016\/j.jelectrocard.2025.154126_bb0050","doi-asserted-by":"crossref","first-page":"6136","DOI":"10.3390\/s21186136","article-title":"A comprehensive review of techniques for processing and analyzing fetal heart rate signals","volume":"21","author":"Ponsiglione","year":"2021","journal-title":"Sensors"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0055","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11886-020-01317-x","article-title":"Artificial intelligence-enabled ECG: a modern lens on an old technology","volume":"22","author":"Kashou","year":"2020","journal-title":"Curr Cardiol Rep"},{"issue":"10","key":"10.1016\/j.jelectrocard.2025.154126_bb0060","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6579\/ac2c5b","article-title":"Fetal ECG extraction using short time Fourier transform and generative adversarial networks","volume":"42","author":"Zhong","year":"2021","journal-title":"Physiol Meas"},{"issue":"1","key":"10.1016\/j.jelectrocard.2025.154126_bb0065","doi-asserted-by":"crossref","first-page":"1711618","DOI":"10.1080\/16549716.2020.1711618","article-title":"Fetal heart rate monitoring practices at a public hospital in northern Uganda\u2013what health workers document, do and say","volume":"13","author":"Ayebare","year":"2020","journal-title":"Glob Health Action"},{"issue":"1","key":"10.1016\/j.jelectrocard.2025.154126_bb0070","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1038\/s41597-021-00811-3","article-title":"A non-invasive multimodal foetal ECG\u2013Doppler dataset for antenatal cardiology research","volume":"8","author":"Sulas","year":"2021","journal-title":"Sci Data"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2021.103187","article-title":"Fetal heart rate estimation by non-invasive single abdominal electrocardiography in real clinical conditions","volume":"71","author":"Dia","year":"2022","journal-title":"Biomed Signal Process Control"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0080","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpbup.2023.100096","article-title":"Semi-supervised active transfer learning for fetal ECG arrhythmia detection","volume":"3","author":"Mohebbian","year":"2023","journal-title":"Comput Methods Program Biomed Update"},{"issue":"9","key":"10.1016\/j.jelectrocard.2025.154126_bb0085","doi-asserted-by":"crossref","first-page":"7200","DOI":"10.1016\/j.jksuci.2022.07.002","article-title":"An IoMT enabled deep learning framework for automatic detection of fetal QRS: a solution to remote prenatal care","volume":"34","author":"Krupa","year":"2022","journal-title":"J King Saud Univ Comput Inform Sci"},{"issue":"1","key":"10.1016\/j.jelectrocard.2025.154126_bb0090","doi-asserted-by":"crossref","first-page":"48","DOI":"10.3390\/bioengineering10010048","article-title":"Fetal arrhythmia detection based on labeling considering heartbeat interval","volume":"10","author":"Nakatani","year":"2022","journal-title":"Bioengineering"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0095","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.105713","article-title":"Binarized spiking neural network optimized with momentum search algorithm for fetal arrhythmia detection and classification from ECG signals","volume":"89","author":"Shekhawat","year":"2024","journal-title":"Biomed Signal Process Control"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0100","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2022.104191","article-title":"Non-invasive diagnosis of fetal arrhythmia based on multi-domain feature and hierarchical extreme learning machine","volume":"79","author":"Liu","year":"2023","journal-title":"Biomed Signal Process Control"},{"issue":"5","key":"10.1016\/j.jelectrocard.2025.154126_bb0105","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1109\/TBCAS.2022.3204993","article-title":"Extraction of fetal ECG from abdominal and thorax ECG using a non-causal adaptive filter architecture","volume":"16","author":"Dhas","year":"2022","journal-title":"IEEE Trans Biomed Circ Syst"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0110","doi-asserted-by":"crossref","DOI":"10.1016\/j.dsp.2021.103090","article-title":"Fractional Stockwell transform: theory and applications","volume":"115","author":"Wei","year":"2021","journal-title":"Digit Signal Process"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0115","first-page":"1428","article-title":"Bacterial colony classification using atrous convolution with transfer learning","author":"Patel","year":"2021","journal-title":"Ann Roman Soc Cell Biol"},{"issue":"4","key":"10.1016\/j.jelectrocard.2025.154126_bb0125","first-page":"417","article-title":"Fetal ECG arrhythmia detection based on DensNet transfer learning","volume":"10","author":"Rai","year":"2023","journal-title":"Front Biomed Technol"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0130","article-title":"Ensemble feature extraction-based prediction of fetal arrhythmia using cardiotocographic signals","volume":"25","author":"Magesh","year":"2023","journal-title":"Measurement: Sensors"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0135","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.121196","article-title":"A novel deep learning technique for morphology preserved fetal ECG extraction from mother ECG using 1D-CycleGAN","volume":"235","author":"Basak","year":"2024","journal-title":"Expert Syst Appl"},{"issue":"1","key":"10.1016\/j.jelectrocard.2025.154126_bb0140","article-title":"Arrhythmia foetus heartbeat detection using optimized neural network based on phonocardiograph ensemble feature and principal component analysis","volume":"16","author":"Faradisa","year":"2023","journal-title":"Int J Intell Eng Syst"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0145","series-title":"In 2023 computing in cardiology (CinC)","first-page":"1","article-title":"Fetal arrhythmia: Deep learning and clustering techniques, analysis through permutation entropy and genetic algorithms in its early diagnosis","volume":"vol. 50","author":"Valdez","year":"2023"},{"issue":"4","key":"10.1016\/j.jelectrocard.2025.154126_bb0150","doi-asserted-by":"crossref","first-page":"1987","DOI":"10.11591\/eei.v10i4.3060","article-title":"Convolutional neural network for semantic segmentation of fetal echocardiography based on four-chamber view","volume":"10","author":"Rachmatullah","year":"2021","journal-title":"Bull Electric Eng Inform"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0155","series-title":"International conference on pattern recognition","first-page":"49","article-title":"MFConvTr: Multi-frequency convolutional transformer for fetal arrhythmia detection in non-invasive fECG","author":"Chintapenta","year":"2024"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0160","doi-asserted-by":"crossref","first-page":"6729","DOI":"10.1109\/ACCESS.2025.3526586","article-title":"Enhanced fetal arrhythmia classification by non-invasive ECG using cross domain feature and spatial differences windows information","volume":"13","author":"Pradipta","year":"2025","journal-title":"IEEE Access"},{"key":"10.1016\/j.jelectrocard.2025.154126_bb0165","doi-asserted-by":"crossref","first-page":"69438","DOI":"10.1109\/ACCESS.2025.3561848","article-title":"FAViTNet: an effective deep learning framework for non-invasive fetal arrhythmia diagnosis","volume":"13","author":"Samuel","year":"2025","journal-title":"IEEE Access"},{"issue":"5","key":"10.1016\/j.jelectrocard.2025.154126_bb0170","doi-asserted-by":"crossref","first-page":"3427","DOI":"10.1109\/JBHI.2025.3528565","article-title":"Adjacent channel weight dependable RLS adaptive filter with VMD based artifact removal mechanism in fetal ECG separation","volume":"29","author":"Dhas","year":"2025","journal-title":"IEEE J Biomed Health Inform"},{"issue":"18","key":"10.1016\/j.jelectrocard.2025.154126_bb0175","doi-asserted-by":"crossref","first-page":"55011","DOI":"10.1007\/s11042-023-17305-6","article-title":"Enhancing fetal electrocardiogram classification: a hybrid approach incorporating multimodal data fusion and advanced deep learning models","volume":"83","author":"Ziani","year":"2024","journal-title":"Multimed Tools Appl"},{"issue":"13","key":"10.1016\/j.jelectrocard.2025.154126_bb0180","first-page":"39755","article-title":"Time-scale image analysis for detection of fetal electrocardiogram","volume":"83","author":"M","year":"2024","journal-title":"Multimed Tools Appl"}],"container-title":["Journal of Electrocardiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0022073625002547?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0022073625002547?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,2,18]],"date-time":"2026-02-18T05:35:39Z","timestamp":1771392939000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0022073625002547"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11]]},"references-count":35,"alternative-id":["S0022073625002547"],"URL":"https:\/\/doi.org\/10.1016\/j.jelectrocard.2025.154126","relation":{},"ISSN":["0022-0736"],"issn-type":[{"value":"0022-0736","type":"print"}],"subject":[],"published":{"date-parts":[[2025,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"An integrated fractional stockwell transform with atrous convolutions aided vision transformer based capsule network for fetal ECG arrhythmia detection","name":"articletitle","label":"Article Title"},{"value":"Journal of Electrocardiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jelectrocard.2025.154126","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"154126"}}