{"id":"https://openalex.org/W4405707321","doi":"https://doi.org/10.1186/s13634-024-01196-2","title":"A blind extraction method of fetal electrocardiogram signal based on MNCMD-NLBCA","display_name":"A blind extraction method of fetal electrocardiogram signal based on MNCMD-NLBCA","publication_year":2024,"publication_date":"2024-12-23","ids":{"openalex":"https://openalex.org/W4405707321","doi":"https://doi.org/10.1186/s13634-024-01196-2"},"language":"en","primary_location":{"id":"doi:10.1186/s13634-024-01196-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-024-01196-2","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-024-01196-2","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1110-8657","issn":["1110-8657","1687-0433","1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-024-01196-2","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065725707","display_name":"Mingyang Tang","orcid":"https://orcid.org/0000-0001-9676-0087"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"MingYang Tang","raw_affiliation_strings":["College of Energy and Power, Northwestern Polytechnical University, Xi\u2019an, 710129, Shaanxi, China","College of Energy and Power, Northwestern Polytechnical University, Xi'an, 710129, Shaanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Energy and Power, Northwestern Polytechnical University, Xi\u2019an, 710129, Shaanxi, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"College of Energy and Power, Northwestern Polytechnical University, Xi'an, 710129, Shaanxi, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103283948","display_name":"Yafeng Wu","orcid":"https://orcid.org/0000-0002-0184-0234"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"YaFeng Wu","raw_affiliation_strings":["College of Energy and Power, Northwestern Polytechnical University, Xi\u2019an, 710129, Shaanxi, China","College of Energy and Power, Northwestern Polytechnical University, Xi'an, 710129, Shaanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Energy and Power, Northwestern Polytechnical University, Xi\u2019an, 710129, Shaanxi, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"College of Energy and Power, Northwestern Polytechnical University, Xi'an, 710129, Shaanxi, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5103283948"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":{"value":1790,"currency":"USD","value_usd":1790},"apc_paid":{"value":1790,"currency":"USD","value_usd":1790},"fwci":0.611,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66101188,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"2024","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9993000030517578,"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":0.9991999864578247,"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":0.9901999831199646,"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/computer-science","display_name":"Computer science","score":0.6006878018379211},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5150513648986816},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.48887795209884644},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.464922696352005},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.43054407835006714},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.426395058631897},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39598697423934937},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38014236092567444},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.21292373538017273},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.20266810059547424},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.1300523579120636},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.07278048992156982},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.06935542821884155},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.06908497214317322}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6006878018379211},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5150513648986816},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.48887795209884644},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.464922696352005},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.43054407835006714},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.426395058631897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39598697423934937},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38014236092567444},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.21292373538017273},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.20266810059547424},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.1300523579120636},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.07278048992156982},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.06935542821884155},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.06908497214317322},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s13634-024-01196-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-024-01196-2","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-024-01196-2","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1110-8657","issn":["1110-8657","1687-0433","1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d76b150c3f604b3d947d6c57e2426250","is_oa":false,"landing_page_url":"https://doaj.org/article/d76b150c3f604b3d947d6c57e2426250","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EURASIP Journal on Advances in Signal Processing, Vol 2024, Iss 1, Pp 1-20 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s13634-024-01196-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-024-01196-2","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-024-01196-2","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1110-8657","issn":["1110-8657","1687-0433","1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","display_name":"Gender equality","score":0.4300000071525574}],"awards":[{"id":"https://openalex.org/G4822318222","display_name":null,"funder_award_id":"2023YFB3208500","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405707321.pdf","grobid_xml":"https://content.openalex.org/works/W4405707321.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W2031125960","https://openalex.org/W2050895000","https://openalex.org/W2083651472","https://openalex.org/W2085258673","https://openalex.org/W2092073195","https://openalex.org/W2093161500","https://openalex.org/W2120006607","https://openalex.org/W2130590697","https://openalex.org/W2131408671","https://openalex.org/W2153738290","https://openalex.org/W2156436462","https://openalex.org/W2157205559","https://openalex.org/W2162800060","https://openalex.org/W2337770506","https://openalex.org/W2607867882","https://openalex.org/W2614141523","https://openalex.org/W2736989556","https://openalex.org/W2785145927","https://openalex.org/W2888325708","https://openalex.org/W2944615888","https://openalex.org/W2981592454","https://openalex.org/W2995628690","https://openalex.org/W2997681386","https://openalex.org/W3028898238","https://openalex.org/W3093909567","https://openalex.org/W3126559606","https://openalex.org/W3210456060","https://openalex.org/W4205708656","https://openalex.org/W4248544668","https://openalex.org/W4311556848","https://openalex.org/W4313480672","https://openalex.org/W4322737601","https://openalex.org/W4362705033","https://openalex.org/W4367845469","https://openalex.org/W4387364945","https://openalex.org/W4388908027"],"related_works":["https://openalex.org/W2383482627","https://openalex.org/W2392054573","https://openalex.org/W2162758065","https://openalex.org/W2997589526","https://openalex.org/W4289145503","https://openalex.org/W2099940608","https://openalex.org/W2889447638","https://openalex.org/W2387756483","https://openalex.org/W2170833027","https://openalex.org/W2362299104"],"abstract_inverted_index":{"Fetal":[0],"electrocardiogram":[1,13,159,203],"signal":[2,14,74,86,117,136],"extraction":[3,15,42],"has":[4,127],"very":[5],"important":[6],"clinical":[7],"significance.":[8],"Currently,":[9],"most":[10],"existing":[11],"fetal":[12,158,202],"algorithms":[16],"are":[17,186],"designed":[18],"for":[19,103],"ideal":[20,38],"positive":[21,96],"definite":[22],"linear":[23,113],"instantaneous":[24],"mixed":[25],"models,":[26],"but":[27],"the":[28,37,41,72,85,91,108,116,121,147,175,184],"actual":[29],"collected":[30],"observation":[31],"signals":[32],"often":[33,44],"do":[34],"not":[35,134],"meet":[36],"standards.":[39],"Therefore,":[40],"results":[43,172],"have":[45],"many":[46],"problems":[47],"such":[48],"as":[49],"inaccurate":[50],"cycles,":[51],"low":[52],"correct":[53],"recognition":[54],"rates,":[55],"resource":[56],"waste,":[57],"and":[58,83,132,168,180,189,198],"time":[59],"consumption.":[60],"This":[61,144],"article":[62,145],"proposes":[63],"an":[64],"underdetermined":[65,93,150],"nonlinear":[66,79,104,109,151],"bounded":[67,122,152],"component":[68,123,153],"analysis":[69,124,154],"method.":[70],"Firstly,":[71],"observed":[73],"is":[75,87,101,118],"processed":[76],"using":[77,120],"multivariate":[78],"chirp":[80],"mode":[81],"decomposition,":[82],"then":[84],"reconstructed":[88],"to":[89,106,138],"convert":[90,107],"original":[92],"situation":[94],"into":[95,111],"definite;":[97],"Then,":[98],"Gaussian":[99],"technique":[100],"used":[102],"compensation":[105],"model":[110],"a":[112],"model;":[114],"Finally,":[115],"extracted":[119],"method,":[125],"which":[126,192],"more":[128],"relaxed":[129],"constraint":[130],"assumptions":[131],"does":[133],"require":[135],"sources":[137],"be":[139],"independent":[140],"of":[141,149,183],"each":[142],"other.":[143],"investigates":[146],"role":[148],"methods":[155],"in":[156],"extracting":[157],"signals.":[160,204],"The":[161,170],"experimental":[162,171],"dataset":[163],"mainly":[164],"uses":[165],"MIT-BIH,":[166],"ADFECGD,":[167],"PCCDB.":[169],"show":[173],"that":[174,194],"average":[176],"similarity":[177],"coefficient,":[178],"MSE":[179],"SIR":[181],"values":[182],"algorithm":[185],"0.969,":[187],"0.023":[188],"12.85,":[190],"respectively,":[191],"proves":[193],"it":[195],"can":[196],"quickly":[197],"effectively":[199],"extract":[200],"clearer":[201]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}