{"id":"https://openalex.org/W3033684251","doi":"https://doi.org/10.1109/access.2020.2998788","title":"DeepArrNet: An Efficient Deep CNN Architecture for Automatic Arrhythmia Detection and Classification From Denoised ECG Beats","display_name":"DeepArrNet: An Efficient Deep CNN Architecture for Automatic Arrhythmia Detection and Classification From Denoised ECG Beats","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3033684251","doi":"https://doi.org/10.1109/access.2020.2998788","mag":"3033684251"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2998788","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2998788","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09104710.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09104710.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014251585","display_name":"Tanvir Mahmud","orcid":"https://orcid.org/0000-0003-0529-2826"},"institutions":[{"id":"https://openalex.org/I183697816","display_name":"Bangladesh University of Engineering and Technology","ror":"https://ror.org/05a1qpv97","country_code":"BD","type":"education","lineage":["https://openalex.org/I183697816"]}],"countries":["BD"],"is_corresponding":true,"raw_author_name":"Tanvir Mahmud","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh","institution_ids":["https://openalex.org/I183697816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074606314","display_name":"Shaikh Anowarul Fattah","orcid":"https://orcid.org/0000-0001-8090-2327"},"institutions":[{"id":"https://openalex.org/I183697816","display_name":"Bangladesh University of Engineering and Technology","ror":"https://ror.org/05a1qpv97","country_code":"BD","type":"education","lineage":["https://openalex.org/I183697816"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Shaikh Anowarul Fattah","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh","institution_ids":["https://openalex.org/I183697816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085448346","display_name":"Mohammad Saquib","orcid":"https://orcid.org/0000-0002-9641-2397"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammad Saquib","raw_affiliation_strings":["Department of Electrical Engineering, The University of Texas at Dallas, Richardson, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, The University of Texas at Dallas, Richardson, USA","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5014251585"],"corresponding_institution_ids":["https://openalex.org/I183697816"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.6001,"has_fulltext":true,"cited_by_count":67,"citation_normalized_percentile":{"value":0.97738518,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"8","issue":null,"first_page":"104788","last_page":"104800"},"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":0.9986000061035156,"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":0.9825000166893005,"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/computer-science","display_name":"Computer science","score":0.7809957265853882},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.7449463605880737},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.7182324528694153},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7056424021720886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6934634447097778},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6899200677871704},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6892882585525513},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5147985816001892},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46491295099258423},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3725796937942505},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.265286386013031},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1514902114868164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7809957265853882},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.7449463605880737},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7182324528694153},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7056424021720886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6934634447097778},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6899200677871704},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6892882585525513},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5147985816001892},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46491295099258423},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3725796937942505},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.265286386013031},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1514902114868164},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2998788","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2998788","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09104710.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c511eda4b73e4a5f94343f1370b195cb","is_oa":true,"landing_page_url":"https://doaj.org/article/c511eda4b73e4a5f94343f1370b195cb","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 104788-104800 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2998788","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2998788","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09104710.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.41999998688697815,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3033684251.pdf","grobid_xml":"https://content.openalex.org/works/W3033684251.grobid-xml"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W1677182931","https://openalex.org/W1889104906","https://openalex.org/W1969943621","https://openalex.org/W2011445508","https://openalex.org/W2015242484","https://openalex.org/W2026775633","https://openalex.org/W2034069945","https://openalex.org/W2034365922","https://openalex.org/W2035381272","https://openalex.org/W2049001165","https://openalex.org/W2062014239","https://openalex.org/W2063923412","https://openalex.org/W2074820813","https://openalex.org/W2076360516","https://openalex.org/W2080883481","https://openalex.org/W2091076299","https://openalex.org/W2095409369","https://openalex.org/W2095705004","https://openalex.org/W2108078404","https://openalex.org/W2118545728","https://openalex.org/W2125654608","https://openalex.org/W2157209869","https://openalex.org/W2251133041","https://openalex.org/W2291961022","https://openalex.org/W2330219538","https://openalex.org/W2482102801","https://openalex.org/W2531409750","https://openalex.org/W2601104861","https://openalex.org/W2611453176","https://openalex.org/W2748902594","https://openalex.org/W2753762384","https://openalex.org/W2795340004","https://openalex.org/W2796659423","https://openalex.org/W2798651459","https://openalex.org/W2801051711","https://openalex.org/W2883780447","https://openalex.org/W2902644322","https://openalex.org/W2949795958","https://openalex.org/W2953333557","https://openalex.org/W2963733370","https://openalex.org/W2964309882","https://openalex.org/W2965380104","https://openalex.org/W2985440675","https://openalex.org/W2995015130","https://openalex.org/W2999971999","https://openalex.org/W3015537910","https://openalex.org/W3098026853","https://openalex.org/W3103507112","https://openalex.org/W3106455851","https://openalex.org/W4241637638","https://openalex.org/W4244802594","https://openalex.org/W4297775537","https://openalex.org/W6631943919","https://openalex.org/W6674330103","https://openalex.org/W6737664043","https://openalex.org/W6748481559","https://openalex.org/W6750097528","https://openalex.org/W6751203130","https://openalex.org/W6765069029","https://openalex.org/W6766273390","https://openalex.org/W6769971416","https://openalex.org/W6786121251"],"related_works":["https://openalex.org/W4361003569","https://openalex.org/W2981421796","https://openalex.org/W2964954556","https://openalex.org/W3034421924","https://openalex.org/W2982536526","https://openalex.org/W4386858688","https://openalex.org/W4380302312","https://openalex.org/W3008689640","https://openalex.org/W4390971171","https://openalex.org/W4385338604"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"an":[3],"efficient":[4,164],"deep":[5,101],"convolutional":[6,195],"neural":[7,102],"network":[8,103],"(CNN)":[9],"architecture":[10,104,184],"is":[11,36,54,77,105],"proposed":[12,110,219],"based":[13,107],"on":[14,108,211],"depthwise":[15,83,128,146],"temporal":[16,84,129,147,191,204],"convolution":[17],"along":[18,92,134],"with":[19,79,86,93,135,151],"a":[20,50,58,100],"robust":[21],"end-to-end":[22],"scheme":[23,53,220],"to":[24,159,177,188,216],"automatically":[25],"detect":[26],"and":[27,95],"classify":[28],"arrhythmia":[29],"from":[30,199],"denoised":[31,47],"electrocardiogram":[32],"(ECG)":[33],"signal,":[34],"which":[35],"termed":[37],"as":[38,63,65],"\u2018DeepArrNet\u2019.":[39],"Firstly,":[40],"considering":[41],"the":[42,109,124,136,161,171,179,186,190,218],"variational":[43],"pattern":[44],"of":[45,115],"wavelet":[46],"ECG":[48],"data,":[49],"realistic":[51],"augmentation":[52],"designed":[55,78],"that":[56,221],"offers":[57],"reduction":[59],"in":[60,131,155,170,193,223,226],"class":[61],"imbalance":[62],"well":[64],"increased":[66,180],"data":[67],"variations.":[68],"A":[69],"structural":[70,111,117,157],"unit,":[71,76],"namely":[72],"PTP":[73],"(Pontwise-Temporal-Pointwise":[74],"Convolution)":[75],"its":[80],"variants":[81],"where":[82,113],"convolutions":[85,130,148,167],"varying":[87,152],"kernel":[88,125,153],"sizes":[89,126,154],"are":[90,119,149,168,208],"incorporated":[91],"prior":[94],"post":[96],"pointwise":[97],"convolution.":[98],"Afterward,":[99],"constructed":[106],"unit":[112,158],"series":[114],"such":[116],"units":[118,133,140,176],"stacked":[120],"together":[121],"while":[122,165],"increasing":[123],"for":[127],"successive":[132],"residual":[137,172],"linkage":[138,173],"between":[139,174,194],"through":[141],"feature":[142],"addition.":[143],"Moreover,":[144],"multiple":[145],"introduced":[150],"each":[156],"make":[160],"process":[162],"more":[163,197],"strided":[166],"utilized":[169],"subsequent":[175],"compensate":[178],"computational":[181],"complexity.":[182],"This":[183],"provides":[185],"opportunity":[187],"explore":[189],"features":[192],"layers":[196],"optimally":[198],"different":[200],"perspectives":[201],"utilizing":[202],"diversified":[203],"kernels.":[205],"Extensive":[206],"experimentations":[207],"carried":[209],"out":[210],"two":[212],"publicly":[213],"available":[214],"datasets":[215],"validate":[217],"results":[222],"outstanding":[224],"performances":[225],"all":[227],"traditional":[228],"evaluation":[229],"metrics":[230],"outperforming":[231],"other":[232],"state-of-the-art":[233],"approaches.":[234]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":5}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
