{"id":"https://openalex.org/W2899166476","doi":"https://doi.org/10.1109/embc.2018.8513495","title":"A Fast Principal Component Analysis Method For Calculating The ECG Derived Respiration","display_name":"A Fast Principal Component Analysis Method For Calculating The ECG Derived Respiration","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2899166476","doi":"https://doi.org/10.1109/embc.2018.8513495","mag":"2899166476","pmid":"https://pubmed.ncbi.nlm.nih.gov/30441532"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2018.8513495","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2018.8513495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 40th Annual International Conference of the IEEE Engineering in Medicine and 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/A5041643564","display_name":"Nadi Sadr","orcid":"https://orcid.org/0000-0001-9926-0678"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Nadi Sadr","raw_affiliation_strings":["The University of Sydney, Sydney, NSW, AU"],"affiliations":[{"raw_affiliation_string":"The University of Sydney, Sydney, NSW, AU","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078054483","display_name":"Philip de Chazal","orcid":"https://orcid.org/0000-0002-2091-207X"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Philip de Chazal","raw_affiliation_strings":["The University of Sydney, Sydney, NSW, AU"],"affiliations":[{"raw_affiliation_string":"The University of Sydney, Sydney, NSW, AU","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5041643564"],"corresponding_institution_ids":["https://openalex.org/I129604602"],"apc_list":null,"apc_paid":null,"fwci":0.5081,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.64564103,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"2018","issue":null,"first_page":"5294","last_page":"5297"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9986000061035156,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9950000047683716,"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/principal-component-analysis","display_name":"Principal component analysis","score":0.8745335340499878},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.700061023235321},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.685997724533081},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6736147403717041},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6478869915008545},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.607806384563446},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5306127667427063},{"id":"https://openalex.org/keywords/sleep-apnea","display_name":"Sleep apnea","score":0.5053272843360901},{"id":"https://openalex.org/keywords/apnea","display_name":"Apnea","score":0.48761239647865295},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.40436986088752747},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2649909257888794},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.09508350491523743},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.07731255888938904},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.06340047717094421}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.8745335340499878},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.700061023235321},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.685997724533081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6736147403717041},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6478869915008545},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.607806384563446},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5306127667427063},{"id":"https://openalex.org/C2777935920","wikidata":"https://www.wikidata.org/wiki/Q213600","display_name":"Sleep apnea","level":2,"score":0.5053272843360901},{"id":"https://openalex.org/C2781326671","wikidata":"https://www.wikidata.org/wiki/Q754424","display_name":"Apnea","level":2,"score":0.48761239647865295},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.40436986088752747},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2649909257888794},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09508350491523743},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.07731255888938904},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.06340047717094421}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"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":"D012119","descriptor_name":"Respiration","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012119","descriptor_name":"Respiration","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012119","descriptor_name":"Respiration","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D025341","descriptor_name":"Principal Component Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D025341","descriptor_name":"Principal Component Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D025341","descriptor_name":"Principal Component Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc.2018.8513495","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2018.8513495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:30441532","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30441532","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":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W97568584","https://openalex.org/W1494365440","https://openalex.org/W1554944419","https://openalex.org/W1601795611","https://openalex.org/W1964357740","https://openalex.org/W1990729619","https://openalex.org/W2021717932","https://openalex.org/W2045259847","https://openalex.org/W2106336403","https://openalex.org/W2121209008","https://openalex.org/W2128261760","https://openalex.org/W2138061685","https://openalex.org/W2140095548","https://openalex.org/W2149298154","https://openalex.org/W2151317568","https://openalex.org/W2153635508","https://openalex.org/W2162800060","https://openalex.org/W2164179736","https://openalex.org/W2171033594","https://openalex.org/W2535971517","https://openalex.org/W4285719527","https://openalex.org/W6603931332","https://openalex.org/W6678375360"],"related_works":["https://openalex.org/W2052589448","https://openalex.org/W2765337000","https://openalex.org/W3104072235","https://openalex.org/W2391447249","https://openalex.org/W2312955079","https://openalex.org/W2350996391","https://openalex.org/W2066119650","https://openalex.org/W2059615944","https://openalex.org/W4224057882","https://openalex.org/W1993173579"],"abstract_inverted_index":{"In":[0,19],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5],"principal":[6],"component":[7],"analysis":[8],"(PCA)":[9],"method":[10,26,50,93,111,127],"for":[11,41,55],"estimating":[12],"the":[13,56,69,74,97,113,124],"respiration":[14],"from":[15,68],"overnight":[16],"ECG":[17,45,57,135],"recording.":[18],"comparison":[20],"to":[21,30,51,62,88,130,133],"other":[22],"published":[23],"methods,":[24],"our":[25,49],"is":[27,128],"very":[28],"fast":[29,125],"compute":[31],"and":[32,82],"has":[33],"low":[34],"memory":[35],"requirements,":[36],"which":[37,58],"makes":[38],"it":[39],"suitable":[40],"processing":[42],"long":[43,134],"duration":[44],"recordings.":[46,136],"We":[47,121],"used":[48,61,87],"derive":[52],"respiratory":[53],"features":[54],"were":[59,86],"then":[60],"identify":[63],"epochs":[64],"of":[65,116],"sleep":[66,90],"apnoea":[67],"ECG.":[70],"Three":[71],"classifiers":[72],"including":[73],"extreme":[75],"learning":[76],"machine":[77,85],"(ELM),":[78],"linear":[79],"discriminant":[80],"analysis,":[81],"support":[83],"vector":[84],"detect":[89],"apnoea.":[91],"The":[92],"was":[94,104],"evaluated":[95,105],"on":[96],"MIT":[98],"PhysioNet":[99],"Apnea-ECG":[100],"database.":[101],"Apnoea":[102],"detection":[103],"with":[106],"leave-one-record-out":[107],"cross-validation.":[108],"Our":[109],"PCA":[110,126,132],"obtained":[112],"highest":[114],"accuracy":[115],"74%":[117],"by":[118],"ELM":[119],"classifier.":[120],"conclude":[122],"that":[123],"useful":[129],"apply":[131]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
