{"id":"https://openalex.org/W4285161189","doi":"https://doi.org/10.1109/tim.2022.3186355","title":"Multilevel Classification and Detection of Cardiac Arrhythmias With High-Resolution Superlet Transform and Deep Convolution Neural Network","display_name":"Multilevel Classification and Detection of Cardiac Arrhythmias With High-Resolution Superlet Transform and Deep Convolution Neural Network","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285161189","doi":"https://doi.org/10.1109/tim.2022.3186355"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3186355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3186355","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","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/A5102872434","display_name":"Prashant Mani Tripathi","orcid":"https://orcid.org/0000-0002-8960-8260"},"institutions":[{"id":"https://openalex.org/I3129773123","display_name":"Bennett University","ror":"https://ror.org/00an5hx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I3129773123"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Prashant Mani Tripathi","raw_affiliation_strings":["Department of Electronics and Communication Engineering, Bennett University, Greater Noida, India"],"raw_orcid":"https://orcid.org/0000-0002-8960-8260","affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, Bennett University, Greater Noida, India","institution_ids":["https://openalex.org/I3129773123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102881948","display_name":"Ashish Kumar","orcid":"https://orcid.org/0000-0002-8413-1192"},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ashish Kumar","raw_affiliation_strings":["School of Electronics Engineering, Vellore Institute of Technology, Chennai, India"],"raw_orcid":"https://orcid.org/0000-0002-8413-1192","affiliations":[{"raw_affiliation_string":"School of Electronics Engineering, Vellore Institute of Technology, Chennai, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039978431","display_name":"Manjeet Kumar","orcid":null},"institutions":[{"id":"https://openalex.org/I863896202","display_name":"Delhi Technological University","ror":"https://ror.org/01ztcvt22","country_code":"IN","type":"education","lineage":["https://openalex.org/I863896202"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manjeet Kumar","raw_affiliation_strings":["Department of Electronics and Communication Engineering, Delhi Technological University, New Delhi, India"],"raw_orcid":"https://orcid.org/0000-0001-6578-9741","affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, Delhi Technological University, New Delhi, India","institution_ids":["https://openalex.org/I863896202"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013946741","display_name":"Rama Komaragiri","orcid":"https://orcid.org/0000-0002-0468-8506"},"institutions":[{"id":"https://openalex.org/I3129773123","display_name":"Bennett University","ror":"https://ror.org/00an5hx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I3129773123"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rama Komaragiri","raw_affiliation_strings":["Department of Electronics and Communication Engineering, Bennett University, Greater Noida, India"],"raw_orcid":"https://orcid.org/0000-0002-0468-8506","affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, Bennett University, Greater Noida, India","institution_ids":["https://openalex.org/I3129773123"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102872434"],"corresponding_institution_ids":["https://openalex.org/I3129773123"],"apc_list":null,"apc_paid":null,"fwci":9.2438,"has_fulltext":false,"cited_by_count":60,"citation_normalized_percentile":{"value":0.98640007,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9951000213623047,"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/T10217","display_name":"Cardiac electrophysiology and arrhythmias","score":0.9882000088691711,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/atrial-fibrillation","display_name":"Atrial fibrillation","score":0.6822771430015564},{"id":"https://openalex.org/keywords/cardiac-arrhythmia","display_name":"Cardiac arrhythmia","score":0.6418275833129883},{"id":"https://openalex.org/keywords/ventricular-fibrillation","display_name":"Ventricular fibrillation","score":0.6157189607620239},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5362832546234131},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.5352208614349365},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.5072011947631836},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4904646575450897},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.48843398690223694},{"id":"https://openalex.org/keywords/electrocardiography","display_name":"Electrocardiography","score":0.47423097491264343},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47194045782089233},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.470216304063797},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46459054946899414},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.31078529357910156}],"concepts":[{"id":"https://openalex.org/C2779161974","wikidata":"https://www.wikidata.org/wiki/Q815819","display_name":"Atrial fibrillation","level":2,"score":0.6822771430015564},{"id":"https://openalex.org/C2988455589","wikidata":"https://www.wikidata.org/wiki/Q189331","display_name":"Cardiac arrhythmia","level":3,"score":0.6418275833129883},{"id":"https://openalex.org/C2781005686","wikidata":"https://www.wikidata.org/wiki/Q848662","display_name":"Ventricular fibrillation","level":2,"score":0.6157189607620239},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5362832546234131},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.5352208614349365},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.5072011947631836},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4904646575450897},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.48843398690223694},{"id":"https://openalex.org/C2780040984","wikidata":"https://www.wikidata.org/wiki/Q79785","display_name":"Electrocardiography","level":2,"score":0.47423097491264343},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47194045782089233},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.470216304063797},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46459054946899414},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.31078529357910156}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2022.3186355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3186355","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.800000011920929,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W2003087197","https://openalex.org/W2015332508","https://openalex.org/W2034069945","https://openalex.org/W2034907671","https://openalex.org/W2044355963","https://openalex.org/W2063923412","https://openalex.org/W2080613901","https://openalex.org/W2095409369","https://openalex.org/W2097117768","https://openalex.org/W2100158118","https://openalex.org/W2100537461","https://openalex.org/W2145812612","https://openalex.org/W2152702278","https://openalex.org/W2158006878","https://openalex.org/W2202063965","https://openalex.org/W2291961022","https://openalex.org/W2341500107","https://openalex.org/W2482102801","https://openalex.org/W2484581833","https://openalex.org/W2568858846","https://openalex.org/W2602063239","https://openalex.org/W2748902594","https://openalex.org/W2795340004","https://openalex.org/W2799663065","https://openalex.org/W2808354127","https://openalex.org/W2887119478","https://openalex.org/W2891342985","https://openalex.org/W2891344579","https://openalex.org/W2942497026","https://openalex.org/W2949795958","https://openalex.org/W2961638199","https://openalex.org/W2963446712","https://openalex.org/W2972620123","https://openalex.org/W3004063830","https://openalex.org/W3010700465","https://openalex.org/W3014961572","https://openalex.org/W3093086118","https://openalex.org/W3093699748","https://openalex.org/W3096280610","https://openalex.org/W3098026853","https://openalex.org/W3111017824","https://openalex.org/W3113178943","https://openalex.org/W3113968199","https://openalex.org/W3115226550","https://openalex.org/W3118424951","https://openalex.org/W3119740068","https://openalex.org/W3133916378","https://openalex.org/W3152528299","https://openalex.org/W3160765675","https://openalex.org/W3160994088","https://openalex.org/W3164107692","https://openalex.org/W3168861255","https://openalex.org/W3170087560","https://openalex.org/W3185043298","https://openalex.org/W3200430820","https://openalex.org/W3207658986","https://openalex.org/W4205562278","https://openalex.org/W4205839055","https://openalex.org/W4205865450","https://openalex.org/W4289304905","https://openalex.org/W6684191040","https://openalex.org/W6687816896","https://openalex.org/W6756147556"],"related_works":["https://openalex.org/W2530685530","https://openalex.org/W4375868962","https://openalex.org/W2011227383","https://openalex.org/W2088854863","https://openalex.org/W1976719989","https://openalex.org/W2942893872","https://openalex.org/W2065606036","https://openalex.org/W3179495260","https://openalex.org/W3127543252","https://openalex.org/W1940356285"],"abstract_inverted_index":{"Atrial":[0],"fibrillation":[1,4,88],"and":[2,18,29,46,53,61,83,89,131,135,148,173,211,228],"ventricular":[3,90,149,175,229],"are":[5,133],"the":[6,65,108,123,140,160,185,199,215,220],"two":[7],"most":[8],"common":[9],"cardiac":[10,13,31,51,71,85],"arrhythmia.":[11],"These":[12],"arrhythmias":[14,86],"cause":[15],"heart":[16,20,26],"strokes":[17],"other":[19],"complications":[21],"leading":[22],"increased":[23],"risk":[24],"of":[25,96,122,193],"failure.":[27],"Early":[28],"accurate":[30],"arrhythmia":[32,52,162],"detection":[33],"is":[34,43,154],"vital":[35],"to":[36,49,63,80,106,138],"preventing":[37],"various":[38],"heart-related":[39,54],"diseases.":[40,55],"Electrocardiogram":[41],"(ECG)":[42],"a":[44,70,76,93,114],"popular":[45],"reliable":[47],"method":[48,79,153,180,197],"detect":[50,84],"However,":[56],"sometimes":[57],"it":[58,203],"becomes":[59],"difficult":[60],"time-consuming":[62],"interpret":[64],"ECG":[66,97,111,141,157,221],"signal,":[67],"even":[68],"for":[69],"expert.":[72],"This":[73],"study":[74],"proposes":[75],"deep":[77],"learning-based":[78],"effectively":[81],"classify":[82,139],"(atrial":[87],"fibrillation)":[91],"using":[92,156],"time-frequency":[94,117],"spectrogram":[95],"records.":[98],"The":[99,119,151,178,195],"proposed":[100,152,179,196,216],"framework":[101],"utilizes":[102],"superlet":[103],"transform":[104,107],"(SLT)":[105],"one-dimensional":[109],"(1-D)":[110],"signal":[112,222],"into":[113,143,223],"two-dimensional":[115],"(2-D)":[116],"spectrogram.":[118],"last":[120],"layer":[121],"pre-trained":[124],"convolutional":[125],"neural":[126],"networks,":[127],"namely,":[128],"AlexNet,":[129],"GoogLeNet,":[130],"DenseNet,":[132],"modified":[134],"then":[136],"used":[137],"records":[142],"healthy":[144,224],"heart,":[145,225],"atrial":[146,226],"fibrillation,":[147,227],"fibrillation.":[150,230],"tested":[155],"signals":[158],"from":[159],"MIT-BIH":[161,164],"database,":[163,166,168,172],"malignant":[165],"Fantasia":[167],"AF":[169],"termination":[170],"challenge":[171],"CU":[174],"tachyarrhythmia":[176],"database.":[177],"with":[181,188],"DenseNet-201":[182],"architecture":[183],"provides":[184],"best":[186],"performance":[187],"an":[189],"overall":[190],"test":[191],"accuracy":[192],"96.2%.":[194],"reduces":[198],"system":[200,217],"complexity":[201],"as":[202],"does":[204],"not":[205],"require":[206],"noise":[207],"removal,":[208],"hand-crafted":[209],"features,":[210],"beat":[212],"detection.":[213],"Further,":[214],"automatically":[218],"classifies":[219]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":3}],"updated_date":"2026-05-20T08:49:12.498775","created_date":"2025-10-10T00:00:00"}