{"id":"https://openalex.org/W4391249244","doi":"https://doi.org/10.1109/ic3i59117.2023.10397894","title":"Classification of Abnormal and Normal ECG beat Based on Deep Learning Techniques","display_name":"Classification of Abnormal and Normal ECG beat Based on Deep Learning Techniques","publication_year":2023,"publication_date":"2023-09-14","ids":{"openalex":"https://openalex.org/W4391249244","doi":"https://doi.org/10.1109/ic3i59117.2023.10397894"},"language":"en","primary_location":{"id":"doi:10.1109/ic3i59117.2023.10397894","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic3i59117.2023.10397894","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 6th International Conference on Contemporary Computing and Informatics (IC3I)","raw_type":"proceedings-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/A5115604586","display_name":"Neha Kumari","orcid":"https://orcid.org/0000-0003-0135-9034"},"institutions":[{"id":"https://openalex.org/I5847235","display_name":"University of Petroleum and Energy Studies","ror":"https://ror.org/04q2jes40","country_code":"IN","type":"education","lineage":["https://openalex.org/I5847235"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Neha Kumari","raw_affiliation_strings":["School of Computer Science, University of Petroleum and Energy Studies,Systemic Cluster,Bidholi, Dehradun,India","Systemic Cluster, School of Computer Science, University of Petroleum and Energy Studies, Bidholi, Dehradun, India"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Petroleum and Energy Studies,Systemic Cluster,Bidholi, Dehradun,India","institution_ids":["https://openalex.org/I5847235"]},{"raw_affiliation_string":"Systemic Cluster, School of Computer Science, University of Petroleum and Energy Studies, Bidholi, Dehradun, India","institution_ids":["https://openalex.org/I5847235"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021521188","display_name":"Mrinal Goswami","orcid":"https://orcid.org/0000-0001-5856-6830"},"institutions":[{"id":"https://openalex.org/I49068896","display_name":"Assam Down Town University","ror":"https://ror.org/039p5s648","country_code":"IN","type":"education","lineage":["https://openalex.org/I49068896"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mrinal Goswami","raw_affiliation_strings":["Assam Down Town University,Faculty of Engineering,Department of Computer Science &#x0026; Engineering,Panikhaiti, Guwahati,Assam,India"],"affiliations":[{"raw_affiliation_string":"Assam Down Town University,Faculty of Engineering,Department of Computer Science &#x0026; Engineering,Panikhaiti, Guwahati,Assam,India","institution_ids":["https://openalex.org/I49068896"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5115604586"],"corresponding_institution_ids":["https://openalex.org/I5847235"],"apc_list":null,"apc_paid":null,"fwci":0.2268,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62871294,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"422","last_page":"428"},"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":0.9976000189781189,"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":0.9860000014305115,"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":0.9008921384811401},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.702595591545105},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.690537691116333},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6885874271392822},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6058391332626343},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5082070827484131},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.46035879850387573},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.41944634914398193},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.1168520450592041},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06952241063117981}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.9008921384811401},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.702595591545105},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.690537691116333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6885874271392822},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6058391332626343},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5082070827484131},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.46035879850387573},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.41944634914398193},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.1168520450592041},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06952241063117981},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ic3i59117.2023.10397894","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic3i59117.2023.10397894","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 6th International Conference on Contemporary Computing and Informatics (IC3I)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.699999988079071,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1538967293","https://openalex.org/W1988183757","https://openalex.org/W2009811197","https://openalex.org/W2026775633","https://openalex.org/W2072661333","https://openalex.org/W2101166342","https://openalex.org/W2108598243","https://openalex.org/W2117539524","https://openalex.org/W2129090268","https://openalex.org/W2140920882","https://openalex.org/W2169533318","https://openalex.org/W2172135815","https://openalex.org/W2251133041","https://openalex.org/W2742565042","https://openalex.org/W3119740068","https://openalex.org/W3160765675","https://openalex.org/W3185108572","https://openalex.org/W3211064646","https://openalex.org/W4205562278","https://openalex.org/W4293233278"],"related_works":["https://openalex.org/W2530685530","https://openalex.org/W4375868962","https://openalex.org/W2011227383","https://openalex.org/W2088854863","https://openalex.org/W4402568167","https://openalex.org/W3179495260","https://openalex.org/W1976719989","https://openalex.org/W3127543252","https://openalex.org/W2897924318","https://openalex.org/W2138997758"],"abstract_inverted_index":{"Electrocardiogram":[0],"signals":[1],"are":[2,24,46,52],"classified":[3],"as":[4],"abnormal":[5,104],"or":[6],"normal":[7,102],"ECG":[8,79],"signal.":[9],"Both":[10],"the":[11,17,27,109,133,147,154,157,197,205,213,220,232,240,244,247],"MIT-BIH":[12,18],"Arrhythmia":[13],"(BIHA)":[14],"Database":[15,22],"and":[16,30,44,69,103,139,161],"Noise":[19],"Stress":[20],"Test":[21],"(NSTDB)":[23],"used":[25],"for":[26],"model's":[28],"training":[29],"testing":[31],"phases.":[32],"Experimental":[33],"For":[34],"classification":[35,230,241],"of":[36,42,135,156,189,239,246],"arrhythmia":[37],"from":[38],"ECG,":[39],"a":[40,88,124,167,173,200,251],"variety":[41],"tools":[43],"techniques":[45],"available.":[47],"The":[48,222,237],"most":[49],"important":[50],"ones":[51],"methods":[53],"like":[54],"time":[55],"series":[56],"analysis,":[57,59],"spectrogram":[58,209],"scalogram":[60],"analysis":[61],"etc.":[62],"Every":[63],"technology":[64],"has":[65,123],"their":[66],"own":[67],"advantages":[68],"limitations":[70],"that":[71,122,224,243],"must":[72],"be":[73],"considered":[74],"when":[75],"using":[76],"it":[77,163],"in":[78,114,193,250],"signa.":[80],"This":[81],"study's":[82],"main":[83],"goal":[84],"is":[85,112,150,164,176,183,210,254],"to":[86,116,129,186,195,218,229],"create":[87],"computational":[89],"model":[90,216,249],"that,":[91,204],"given":[92],"an":[93,118],"electrocardiogram":[94,119],"(ECG)":[95,120],"signal":[96,121,149,198],"can":[97],"reliably":[98],"categorise":[99,117],"bits":[100],"into":[101,166,212],"class.":[105],"In":[106,144],"this":[107,145],"study,":[108],"proposed":[110,248],"method":[111],"implemented":[113],"order":[115,194],"noise":[125],"levels":[126],"between":[127],"-6":[128],"24":[130],"decibel(dB)":[131],"by":[132,153,180],"use":[134,188],"superlet":[136,158],"transform,":[137],"VGG18,":[138],"K-Nearest":[140,233],"Neighbour":[141,234],"(KNN)":[142,235],"classifier.":[143,236],"regard,":[146],"input":[148],"first":[151],"pre-processed":[152],"application":[155],"transform":[159],"(SLT),":[160],"then":[162],"turned":[165],"2-D":[168,206],"temporal":[169,207],"frequency":[170,208],"spectrogram.":[171],"Because":[172],"bandpass":[174],"filter":[175],"already":[177],"utilised":[178],"internally":[179],"superlet,":[181],"there":[182],"no":[184],"need":[185],"make":[187],"any":[190],"additional":[191],"filters":[192],"exclude":[196],"with":[199],"low":[201],"SNR.":[202],"Following":[203],"fed":[211],"transfer":[214],"learning":[215],"(VGG16)":[217],"extract":[219],"features.":[221],"features":[223],"were":[225,227],"gathered":[226],"subjected":[228],"via":[231],"results":[238],"indicate":[242],"accuracy":[245],"noisy":[252],"environment":[253],"99.46%.":[255]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
