{"id":"https://openalex.org/W4312924492","doi":"https://doi.org/10.1109/iscc55528.2022.9912906","title":"A Deep Learning Based ECG Segmentation Tool for Detection of ECG Beat Parameters","display_name":"A Deep Learning Based ECG Segmentation Tool for Detection of ECG Beat Parameters","publication_year":2022,"publication_date":"2022-06-30","ids":{"openalex":"https://openalex.org/W4312924492","doi":"https://doi.org/10.1109/iscc55528.2022.9912906"},"language":"en","primary_location":{"id":"doi:10.1109/iscc55528.2022.9912906","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscc55528.2022.9912906","pdf_url":null,"source":{"id":"https://openalex.org/S4363605780","display_name":"2022 IEEE Symposium on Computers and Communications (ISCC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Symposium on Computers and Communications (ISCC)","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/A5054889019","display_name":"Muhammad Salman Haleem","orcid":"https://orcid.org/0000-0001-5946-6567"},"institutions":[{"id":"https://openalex.org/I39555362","display_name":"University of Warwick","ror":"https://ror.org/01a77tt86","country_code":"GB","type":"education","lineage":["https://openalex.org/I39555362"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Muhammad Salman Haleem","raw_affiliation_strings":["School of Engineering, University of Warwick,Coventry,UK","School of Engineering, University of Warwick, Coventry, UK"],"affiliations":[{"raw_affiliation_string":"School of Engineering, University of Warwick,Coventry,UK","institution_ids":["https://openalex.org/I39555362"]},{"raw_affiliation_string":"School of Engineering, University of Warwick, Coventry, UK","institution_ids":["https://openalex.org/I39555362"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021472133","display_name":"Leandro Pecchia","orcid":"https://orcid.org/0000-0002-7900-5415"},"institutions":[{"id":"https://openalex.org/I39555362","display_name":"University of Warwick","ror":"https://ror.org/01a77tt86","country_code":"GB","type":"education","lineage":["https://openalex.org/I39555362"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Leandro Pecchia","raw_affiliation_strings":["School of Engineering, University of Warwick,Coventry,UK","School of Engineering, University of Warwick, Coventry, UK"],"affiliations":[{"raw_affiliation_string":"School of Engineering, University of Warwick,Coventry,UK","institution_ids":["https://openalex.org/I39555362"]},{"raw_affiliation_string":"School of Engineering, University of Warwick, Coventry, UK","institution_ids":["https://openalex.org/I39555362"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5054889019"],"corresponding_institution_ids":["https://openalex.org/I39555362"],"apc_list":null,"apc_paid":null,"fwci":2.3708,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.90033784,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9959999918937683,"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":0.9959999918937683,"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":0.9779000282287598,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7887780070304871},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7832258939743042},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7636640071868896},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6056097745895386},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5673872828483582},{"id":"https://openalex.org/keywords/beat","display_name":"Beat (acoustics)","score":0.5497817993164062},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5119622945785522},{"id":"https://openalex.org/keywords/fiducial-marker","display_name":"Fiducial marker","score":0.45636269450187683},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3627524673938751}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7887780070304871},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7832258939743042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7636640071868896},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6056097745895386},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5673872828483582},{"id":"https://openalex.org/C189809214","wikidata":"https://www.wikidata.org/wiki/Q829522","display_name":"Beat (acoustics)","level":2,"score":0.5497817993164062},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5119622945785522},{"id":"https://openalex.org/C173974348","wikidata":"https://www.wikidata.org/wiki/Q1469893","display_name":"Fiducial marker","level":2,"score":0.45636269450187683},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3627524673938751},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iscc55528.2022.9912906","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscc55528.2022.9912906","pdf_url":null,"source":{"id":"https://openalex.org/S4363605780","display_name":"2022 IEEE Symposium on Computers and Communications (ISCC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Symposium on Computers and Communications (ISCC)","raw_type":"proceedings-article"},{"id":"pmh:oai:qmro.qmul.ac.uk:123456789/91648","is_oa":false,"landing_page_url":"https://qmro.qmul.ac.uk/xmlui/handle/123456789/91648","pdf_url":null,"source":{"id":"https://openalex.org/S4306400530","display_name":"Queen Mary Research Online (Queen Mary University of London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I166337079","host_organization_name":"Queen Mary University of London","host_organization_lineage":["https://openalex.org/I166337079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"},{"id":"pmh:oai:wrap.warwick.ac.uk:171101","is_oa":false,"landing_page_url":"https://wrap.warwick.ac.uk/171101/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400665","display_name":"Warwick Research Archive Portal (University of Warwick)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39555362","host_organization_name":"University of Warwick","host_organization_lineage":["https://openalex.org/I39555362"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Item"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2525537761","https://openalex.org/W2072325087","https://openalex.org/W402593573","https://openalex.org/W2905789513","https://openalex.org/W2972424784","https://openalex.org/W1486589819","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983"],"abstract_inverted_index":{"The":[0,115,140],"role":[1],"of":[2,12,18,25,54,79,117,132],"ECG":[3,14,110,119,133,141],"segmentation":[4,120,134,142],"tool":[5,121],"has":[6,122],"been":[7,123],"pivotal":[8],"in":[9,130],"automated":[10],"analysis":[11],"real-time":[13],"signals":[15],"for":[16],"detection":[17,138,149],"non-invasive":[19],"cardiovascular":[20],"and":[21,64,76,105,135],"physiological":[22,81],"conditions.":[23],"Most":[24],"the":[26,52,66,80,88,126],"existing":[27],"approaches":[28,39,129],"focus":[29],"on":[30,44,70,101],"traditional":[31,35],"signal":[32,45],"processing":[33],"and/or":[34],"machine":[36],"learning":[37,56],"based":[38,57,69,90,100],"which":[40],"are":[41],"highly":[42],"dependent":[43],"noise,":[46],"inter/intra":[47],"subject":[48],"variability,":[49],"etc.":[50],"With":[51],"advent":[53],"deep":[55],"networks,":[58],"it":[59],"is":[60],"possible":[61],"to":[62],"design":[63],"develop":[65],"classification":[67],"model":[68],"local":[71,102],"features":[72,104],"along":[73],"with":[74],"spatial":[75],"temporal":[77,106],"context":[78],"signals.":[82],"In":[83],"this":[84],"paper,":[85],"we":[86],"developed":[87],"attention":[89],"Convolutional":[91],"Bidirectional":[92],"Long":[93],"Short":[94],"Term":[95],"Memory":[96],"(Conv-BiLSTM)":[97],"architecture":[98],"network":[99],"beat":[103,111],"sequencing":[107],"while":[108],"correlating":[109],"across":[112],"different":[113],"positions.":[114],"performance":[116],"our":[118],"evaluated":[124],"against":[125],"state-of-the":[127],"art":[128],"terms":[131],"fiducial":[136,147],"point":[137,148],"accuracy.":[139],"accuracy":[143,150],"was":[144,151],"95%":[145],"whereas":[146],"99.4%.":[152]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2023-01-05T00:00:00"}
