{"id":"https://openalex.org/W3188715539","doi":"https://doi.org/10.1109/bhi50953.2021.9508527","title":"Multi-module Recurrent Convolutional Neural Network with Transformer Encoder for ECG Arrhythmia Classification","display_name":"Multi-module Recurrent Convolutional Neural Network with Transformer Encoder for ECG Arrhythmia Classification","publication_year":2021,"publication_date":"2021-07-27","ids":{"openalex":"https://openalex.org/W3188715539","doi":"https://doi.org/10.1109/bhi50953.2021.9508527","mag":"3188715539"},"language":"en","primary_location":{"id":"doi:10.1109/bhi50953.2021.9508527","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bhi50953.2021.9508527","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100558811","display_name":"Minh Duc Hoang Le","orcid":null},"institutions":[{"id":"https://openalex.org/I78715868","display_name":"University of Arkansas at Fayetteville","ror":"https://ror.org/05jbt9m15","country_code":"US","type":"education","lineage":["https://openalex.org/I78715868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Minh Duc Le","raw_affiliation_strings":["University of Arkansas, Fayetteville, AR, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Arkansas, Fayetteville, AR, USA","institution_ids":["https://openalex.org/I78715868"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022963260","display_name":"Vidhiwar Singh Rathour","orcid":null},"institutions":[{"id":"https://openalex.org/I78715868","display_name":"University of Arkansas at Fayetteville","ror":"https://ror.org/05jbt9m15","country_code":"US","type":"education","lineage":["https://openalex.org/I78715868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vidhiwar Singh Rathour","raw_affiliation_strings":["University of Arkansas, Fayetteville, AR, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Arkansas, Fayetteville, AR, USA","institution_ids":["https://openalex.org/I78715868"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014387422","display_name":"Quang Sang Truong","orcid":null},"institutions":[{"id":"https://openalex.org/I78715868","display_name":"University of Arkansas at Fayetteville","ror":"https://ror.org/05jbt9m15","country_code":"US","type":"education","lineage":["https://openalex.org/I78715868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Quang Sang Truong","raw_affiliation_strings":["University of Arkansas, Fayetteville, AR, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Arkansas, Fayetteville, AR, USA","institution_ids":["https://openalex.org/I78715868"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036944630","display_name":"Quan Mai","orcid":null},"institutions":[{"id":"https://openalex.org/I78715868","display_name":"University of Arkansas at Fayetteville","ror":"https://ror.org/05jbt9m15","country_code":"US","type":"education","lineage":["https://openalex.org/I78715868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Quan Mai","raw_affiliation_strings":["University of Arkansas, Fayetteville, AR, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Arkansas, Fayetteville, AR, USA","institution_ids":["https://openalex.org/I78715868"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057882319","display_name":"Patel Brijesh","orcid":null},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Patel Brijesh","raw_affiliation_strings":["School of Medicine, West Virginia University, Morgantown, WV, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Medicine, West Virginia University, Morgantown, WV, USA","institution_ids":["https://openalex.org/I12097938"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023725893","display_name":"Ngan Le","orcid":"https://orcid.org/0000-0003-2571-0511"},"institutions":[{"id":"https://openalex.org/I78715868","display_name":"University of Arkansas at Fayetteville","ror":"https://ror.org/05jbt9m15","country_code":"US","type":"education","lineage":["https://openalex.org/I78715868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ngan Le","raw_affiliation_strings":["University of Arkansas, Fayetteville, AR, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Arkansas, Fayetteville, AR, USA","institution_ids":["https://openalex.org/I78715868"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.8451436758041382},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7481733560562134},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7177760004997253},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6840884685516357},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.586581826210022},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.578167200088501},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5292593240737915},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4855949282646179},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43402668833732605},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.4156845808029175},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33467015624046326},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10801628232002258}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.8451436758041382},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7481733560562134},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7177760004997253},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6840884685516357},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.586581826210022},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.578167200088501},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5292593240737915},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4855949282646179},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43402668833732605},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4156845808029175},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33467015624046326},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10801628232002258},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bhi50953.2021.9508527","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bhi50953.2021.9508527","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1939789023","https://openalex.org/W1971573857","https://openalex.org/W2018276655","https://openalex.org/W2018340928","https://openalex.org/W2064675550","https://openalex.org/W2079735306","https://openalex.org/W2125654608","https://openalex.org/W2157858333","https://openalex.org/W2194775991","https://openalex.org/W2223222085","https://openalex.org/W2291961022","https://openalex.org/W2594015355","https://openalex.org/W2748902594","https://openalex.org/W2766443844","https://openalex.org/W2771148491","https://openalex.org/W2775229114","https://openalex.org/W2795131026","https://openalex.org/W2795340004","https://openalex.org/W2796659423","https://openalex.org/W2807367691","https://openalex.org/W2810123878","https://openalex.org/W2883338911","https://openalex.org/W2884795774","https://openalex.org/W2889838428","https://openalex.org/W2902644322","https://openalex.org/W2919115771","https://openalex.org/W2920950417","https://openalex.org/W2938651781","https://openalex.org/W2949352098","https://openalex.org/W2961638199","https://openalex.org/W2963403868","https://openalex.org/W2984759351","https://openalex.org/W3015226328","https://openalex.org/W3027530687","https://openalex.org/W3035916338","https://openalex.org/W3048153153","https://openalex.org/W3099085560","https://openalex.org/W3103448416","https://openalex.org/W4251241654","https://openalex.org/W4252974092","https://openalex.org/W4385245566","https://openalex.org/W6739901393","https://openalex.org/W6745411574","https://openalex.org/W6750097528","https://openalex.org/W6782308933"],"related_works":["https://openalex.org/W2530685530","https://openalex.org/W4375868962","https://openalex.org/W2011227383","https://openalex.org/W3013693939","https://openalex.org/W2088854863","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W1976719989","https://openalex.org/W2942893872"],"abstract_inverted_index":{"The":[0,225],"automatic":[1],"classification":[2],"of":[3,32,53,66,122,163,177],"electrocardiogram":[4],"(ECG)":[5],"signals":[6],"has":[7,100],"played":[8],"an":[9,146],"important":[10],"role":[11],"in":[12,29,105],"cardiovascular":[13],"diseases":[14],"diagnosis":[15],"and":[16,37,55,69,98,129,187,248],"prediction.":[17],"Deep":[18],"neural":[19],"networks":[20],"(DNNs),":[21],"particularly":[22],"Convolutional":[23,117],"Neural":[24,118,131],"Networks":[25,119,132],"(CNNs),":[26],"have":[27,228],"excelled":[28],"a":[30,51,64,114,203],"variety":[31],"intelligent":[33],"tasks":[34],"including":[35,96],"biomedical":[36],"health":[38],"informatics.":[39],"Most":[40],"the":[41,46,60,77,136,196,213,216,239],"existing":[42],"approaches":[43],"either":[44],"partition":[45],"ECG":[47,61,164,178],"time":[48,165],"series":[49],"into":[50,63],"set":[52,65],"segments":[54,84],"apply":[56,70],"1D-CNNs":[57],"or":[58,85],"divide":[59],"signal":[62],"spectrogram":[67,168,179],"images":[68],"2D-CNNs.":[71],"These":[72],"studies,":[73],"however,":[74],"suffer":[75],"from":[76,198],"limitation":[78],"that":[79,230],"temporal":[80,137],"dependencies":[81],"between":[82],"1D":[83,157],"2D":[86,171],"spectrograms":[87],"are":[88],"not":[89,101],"considered":[90],"during":[91],"network":[92,223],"construction.":[93],"Furthermore,":[94],"meta-data":[95],"gender":[97,188],"age":[99,186],"been":[102],"well":[103],"studied":[104],"these":[106],"researches.":[107],"To":[108],"address":[109],"those":[110],"limitations,":[111],"we":[112],"propose":[113],"multi-module":[115,140,233],"Recurrent":[116,130],"(RC-NNs)":[120],"consisting":[121],"both":[123],"CNNs":[124],"to":[125,134,211],"learn":[126],"spatial":[127],"representation":[128,176],"(RNNs)":[133],"model":[135],"relationship.":[138],"Our":[139],"RCNNs":[141,158,172,234],"architecture":[142],"is":[143],"designed":[144],"as":[145],"end-to-end":[147],"deep":[148],"framework":[149],"with":[150,235,241],"four":[151],"modules:":[152],"(i)":[153],"time-series":[154],"module":[155,169,183,192],"by":[156,170,202],"which":[159,173,184,193],"extracts":[160],"spatio-temporal":[161],"information":[162,197],"series;":[166],"(ii)":[167],"learns":[174],"visual-temporal":[175],";":[180],"(iii)":[181],"metadata":[182],"vectorizes":[185],"information;":[189],"(iv)":[190],"fusion":[191],"semantically":[194],"fuses":[195],"three":[199],"above":[200],"modules":[201],"transformer":[204,236],"encoder.":[205],"Ten-fold":[206],"cross":[207],"validation":[208],"was":[209],"used":[210],"evaluate":[212],"approach":[214],"on":[215],"MIT-BIH":[217],"arrhythmia":[218],"database":[219],"(MIT-BIH)":[220],"under":[221],"different":[222],"configurations.":[224],"experimental":[226],"results":[227],"proved":[229],"our":[231],"proposed":[232],"encoder":[237],"achieves":[238],"state-of-the-art":[240],"99.14%":[242],"F":[243],"<inf":[244],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[245],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</inf>":[246],"score":[247],"98.29%":[249],"accuracy.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
