{"id":"https://openalex.org/W3082718511","doi":"https://doi.org/10.1109/embc44109.2020.9175998","title":"ECG-Derived Heart Rate Variability Interpolation and 1-D Convolutional Neural Networks for Detecting Sleep Apnea","display_name":"ECG-Derived Heart Rate Variability Interpolation and 1-D Convolutional Neural Networks for Detecting Sleep Apnea","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3082718511","doi":"https://doi.org/10.1109/embc44109.2020.9175998","mag":"3082718511","pmid":"https://pubmed.ncbi.nlm.nih.gov/33018068"},"language":"en","primary_location":{"id":"doi:10.1109/embc44109.2020.9175998","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc44109.2020.9175998","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 42nd Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5023279352","display_name":"Roneel V. Sharan","orcid":"https://orcid.org/0000-0003-1079-8709"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Roneel V. Sharan","raw_affiliation_strings":["Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047191996","display_name":"Shlomo Berkovsky","orcid":"https://orcid.org/0000-0003-2638-4121"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shlomo Berkovsky","raw_affiliation_strings":["Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100604456","display_name":"Hao Xiong","orcid":"https://orcid.org/0000-0002-6842-1667"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hao Xiong","raw_affiliation_strings":["Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088581420","display_name":"Enrico Coiera","orcid":"https://orcid.org/0000-0002-6444-6584"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Enrico Coiera","raw_affiliation_strings":["Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5023279352"],"corresponding_institution_ids":["https://openalex.org/I99043593"],"apc_list":null,"apc_paid":null,"fwci":2.527,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.90185781,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"2020","issue":null,"first_page":"637","last_page":"640"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10234","display_name":"Obstructive Sleep Apnea Research","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"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/T10234","display_name":"Obstructive Sleep Apnea Research","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9983999729156494,"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"}},{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.761703372001648},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7080047726631165},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7071498036384583},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6776732206344604},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6375820636749268},{"id":"https://openalex.org/keywords/sleep-apnea","display_name":"Sleep apnea","score":0.5999601483345032},{"id":"https://openalex.org/keywords/heart-rate-variability","display_name":"Heart rate variability","score":0.5713146924972534},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5234087109565735},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.47634151577949524},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44566336274147034},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4376829266548157},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43070918321609497},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.357477068901062},{"id":"https://openalex.org/keywords/heart-rate","display_name":"Heart rate","score":0.21341416239738464},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.08995282649993896},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07661521434783936},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.07310861349105835}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.761703372001648},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7080047726631165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7071498036384583},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6776732206344604},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6375820636749268},{"id":"https://openalex.org/C2777935920","wikidata":"https://www.wikidata.org/wiki/Q213600","display_name":"Sleep apnea","level":2,"score":0.5999601483345032},{"id":"https://openalex.org/C71635504","wikidata":"https://www.wikidata.org/wiki/Q933954","display_name":"Heart rate variability","level":4,"score":0.5713146924972534},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5234087109565735},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.47634151577949524},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44566336274147034},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4376829266548157},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43070918321609497},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.357477068901062},{"id":"https://openalex.org/C2777953023","wikidata":"https://www.wikidata.org/wiki/Q1073121","display_name":"Heart rate","level":3,"score":0.21341416239738464},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.08995282649993896},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07661521434783936},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.07310861349105835},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006339","descriptor_name":"Heart Rate","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006339","descriptor_name":"Heart Rate","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006339","descriptor_name":"Heart Rate","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012891","descriptor_name":"Sleep Apnea Syndromes","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D012891","descriptor_name":"Sleep Apnea Syndromes","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D012891","descriptor_name":"Sleep Apnea Syndromes","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc44109.2020.9175998","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc44109.2020.9175998","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 42nd Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:33018068","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33018068","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W44341116","https://openalex.org/W1494365440","https://openalex.org/W1522301498","https://openalex.org/W1601795611","https://openalex.org/W1663973292","https://openalex.org/W1665214252","https://openalex.org/W1974618482","https://openalex.org/W2045259847","https://openalex.org/W2071990051","https://openalex.org/W2103647655","https://openalex.org/W2117834225","https://openalex.org/W2149694328","https://openalex.org/W2155758218","https://openalex.org/W2157494358","https://openalex.org/W2160054777","https://openalex.org/W2162800060","https://openalex.org/W2164179736","https://openalex.org/W2343482910","https://openalex.org/W2517389691","https://openalex.org/W2537400565","https://openalex.org/W2546302380","https://openalex.org/W2759190050","https://openalex.org/W2901890644","https://openalex.org/W2964121744","https://openalex.org/W2974597585","https://openalex.org/W6631190155","https://openalex.org/W6637242042","https://openalex.org/W6744482961","https://openalex.org/W6756338335"],"related_works":["https://openalex.org/W4299822940","https://openalex.org/W2279398222","https://openalex.org/W2336974148","https://openalex.org/W3156786002","https://openalex.org/W4366492315","https://openalex.org/W2546942002","https://openalex.org/W2946016983","https://openalex.org/W2772780115","https://openalex.org/W4386066044","https://openalex.org/W2733060750"],"abstract_inverted_index":{"Feature":[0],"extraction":[1,145],"from":[2],"ECG-derived":[3],"heart":[4,101,118],"rate":[5,102,119],"variability":[6,103,120],"signal":[7,89],"has":[8,83],"shown":[9,84],"to":[10,98,122,136],"be":[11],"useful":[12],"in":[13,58,87,184],"classifying":[14],"sleep":[15,73,186],"apnea.":[16],"In":[17,92],"earlier":[18],"works,":[19],"time-domain":[20],"features,":[21,23],"frequency-domain":[22],"and":[24,39,55,129,146,171],"a":[25,107,123,133,156],"combination":[26],"of":[27,66,150,158,181],"the":[28,64,116,137,141,151,169],"two":[29],"have":[30,49],"been":[31],"used":[32,166],"with":[33,163],"classifiers":[34],"such":[35],"as":[36,132],"logistic":[37],"regression":[38],"support":[40],"vector":[41],"machines.":[42],"However,":[43],"more":[44],"recently,":[45],"deep":[46],"learning":[47],"techniques":[48,57],"outperformed":[50],"these":[51],"conventional":[52],"feature":[53,144],"engineering":[54],"classification":[56,80,90],"various":[59,88],"applications.":[60,91],"This":[61],"work":[62],"explores":[63],"use":[65,96],"convolutional":[67],"neural":[68],"networks":[69],"(CNN)":[70],"for":[71,143,167,173],"detecting":[72,185],"apnea":[74,187],"segments.":[75],"CNN":[76,109],"is":[77,153],"an":[78,179],"image":[79],"technique":[81,114],"that":[82],"robust":[85],"performance":[86,149],"this":[93],"work,":[94],"we":[95],"it":[97,131],"classify":[99],"one-dimensional":[100,108],"signal,":[104],"thereby":[105],"utilizing":[106],"(1-D":[110],"CNN).":[111],"The":[112,148,175],"proposed":[113,176],"resizes":[115],"raw":[117],"data":[121],"common":[124],"dimension":[125],"using":[126],"cubic":[127],"interpolation":[128],"uses":[130],"direct":[134],"input":[135],"1-D":[138],"CNN,":[139],"without":[140],"need":[142],"selection.":[147],"method":[152,177],"evaluated":[154],"on":[155],"dataset":[157],"70":[159],"overnight":[160],"ECG":[161],"recordings,":[162],"35":[164,172],"recordings":[165],"training":[168],"model":[170],"testing.":[174],"achieves":[178],"accuracy":[180],"88.23%":[182],"(AUC=0.9453)":[183],"epochs,":[188],"outperforming":[189],"several":[190],"baseline":[191],"techniques.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":5}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}
