{"id":"https://openalex.org/W2902810937","doi":"https://doi.org/10.1109/icfsp.2018.8552074","title":"Fetal QRS Detection Based on Convolutional Neural Networks in Noninvasive Fetal Electrocardiogram","display_name":"Fetal QRS Detection Based on Convolutional Neural Networks in Noninvasive Fetal Electrocardiogram","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2902810937","doi":"https://doi.org/10.1109/icfsp.2018.8552074","mag":"2902810937"},"language":"en","primary_location":{"id":"doi:10.1109/icfsp.2018.8552074","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icfsp.2018.8552074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 4th International Conference on Frontiers of Signal Processing (ICFSP)","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/A5056700972","display_name":"Jun Seong Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jun Seong Lee","raw_affiliation_strings":["Department of Electrical Engineering, POSTECH, Pohang, Gyeongbuk, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, POSTECH, Pohang, Gyeongbuk, Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102025103","display_name":"Minseok Seo","orcid":"https://orcid.org/0000-0002-8711-8428"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minseok Seo","raw_affiliation_strings":["Department of Electrical Engineering, POSTECH, Pohang, Gyeongbuk, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, POSTECH, Pohang, Gyeongbuk, Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100452155","display_name":"Sang Woo Kim","orcid":"https://orcid.org/0000-0001-6023-1837"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sang Woo Kim","raw_affiliation_strings":["Department of Electrical Engineering, POSTECH, Pohang, Gyeongbuk, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, POSTECH, Pohang, Gyeongbuk, Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101744207","display_name":"Minho Choi","orcid":"https://orcid.org/0000-0001-5882-1547"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minho Choi","raw_affiliation_strings":["Department of Creative IT Engineering and Future IT Innovation Laboratory, POSTECH, Pohang, Gyeongbuk, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Creative IT Engineering and Future IT Innovation Laboratory, POSTECH, Pohang, Gyeongbuk, Korea","institution_ids":["https://openalex.org/I123900574"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I123900574"],"apc_list":null,"apc_paid":null,"fwci":5.7308,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.96973865,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"75","last_page":"78"},"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/T11217","display_name":"Cardiac Arrhythmias and Treatments","score":0.9955000281333923,"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory 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/qrs-complex","display_name":"QRS complex","score":0.8556288480758667},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7081928253173828},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.6169513463973999},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5751984119415283},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5346264839172363},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5070600509643555},{"id":"https://openalex.org/keywords/fetus","display_name":"Fetus","score":0.4624142646789551},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.3916422426700592},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2978738844394684},{"id":"https://openalex.org/keywords/pregnancy","display_name":"Pregnancy","score":0.11853459477424622}],"concepts":[{"id":"https://openalex.org/C111773187","wikidata":"https://www.wikidata.org/wiki/Q1969239","display_name":"QRS complex","level":2,"score":0.8556288480758667},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7081928253173828},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.6169513463973999},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5751984119415283},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5346264839172363},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5070600509643555},{"id":"https://openalex.org/C172680121","wikidata":"https://www.wikidata.org/wiki/Q26513","display_name":"Fetus","level":3,"score":0.4624142646789551},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.3916422426700592},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2978738844394684},{"id":"https://openalex.org/C2779234561","wikidata":"https://www.wikidata.org/wiki/Q11995","display_name":"Pregnancy","level":2,"score":0.11853459477424622},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icfsp.2018.8552074","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icfsp.2018.8552074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 4th International Conference on Frontiers of Signal Processing (ICFSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W204095341","https://openalex.org/W1665214252","https://openalex.org/W1982391827","https://openalex.org/W2010755794","https://openalex.org/W2053102966","https://openalex.org/W2065506507","https://openalex.org/W2086903144","https://openalex.org/W2095705004","https://openalex.org/W2108255727","https://openalex.org/W2109913859","https://openalex.org/W2150885915","https://openalex.org/W2151172597","https://openalex.org/W2151545926","https://openalex.org/W2163605009","https://openalex.org/W2167595074","https://openalex.org/W2404692435","https://openalex.org/W2790139067","https://openalex.org/W6637242042","https://openalex.org/W6674330103","https://openalex.org/W6676302446","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W1989053350","https://openalex.org/W3181746755","https://openalex.org/W2521062615","https://openalex.org/W3016958897","https://openalex.org/W2154464465","https://openalex.org/W4303980421","https://openalex.org/W4283379348","https://openalex.org/W4312417841","https://openalex.org/W2767651786","https://openalex.org/W2912288872"],"abstract_inverted_index":{"Detection":[0],"of":[1,46,110,117],"fetal":[2,8,18,48,59,81,127],"QRS":[3,60,82],"complexes":[4,61,83],"in":[5,62,97],"a":[6,36,47],"noninvasive":[7],"electrocardiogram":[9],"(NI-FECG)":[10],"signal":[11,34,39],"is":[12,28,69],"an":[13,54],"important":[14],"task":[15],"to":[16,21,56,125,130],"check":[17,126],"conditions":[19,128],"and":[20,76,113,129],"prevent":[22,131],"birth":[23,132],"defects.":[24,133],"However,":[25],"the":[26,32,58,63,80,86,92,107],"detection":[27],"not":[29],"easy":[30],"because":[31],"NI-FECG":[33,64,94],"contains":[35],"maternal":[37,87],"ECG":[38,49,88],"that":[40,45],"has":[41],"greater":[42],"amplitude":[43],"than":[44],"signal.":[50,65,89],"This":[51],"paper":[52],"proposes":[53],"algorithm":[55,68,105,122],"detect":[57,79],"The":[66,103,120],"proposed":[67,104,121],"based":[70],"on":[71],"convolutional":[72],"neural":[73],"networks":[74],"(CNN)":[75],"can":[77,123],"reliably":[78],"without":[84],"separating":[85],"To":[90],"verify":[91],"algorithm,":[93],"data":[95],"(PhysioNet/computing":[96],"cardiology":[98],"challenge":[99],"2013)":[100],"were":[101],"used.":[102],"showed":[106],"average":[108],"sensitivity":[109],"89.06":[111],"%":[112],"positive":[114],"predictive":[115],"value":[116],"92.77":[118],"%.":[119],"help":[124]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}