{"id":"https://openalex.org/W2854349075","doi":"https://doi.org/10.1109/siu.2018.8404243","title":"Performance evaluation of Empirical Mode Decomposition and Discrete Wavelet Transform for computerized hypoxia detection and prediction","display_name":"Performance evaluation of Empirical Mode Decomposition and Discrete Wavelet Transform for computerized hypoxia detection and prediction","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2854349075","doi":"https://doi.org/10.1109/siu.2018.8404243","mag":"2854349075"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2018.8404243","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2018.8404243","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th Signal Processing and Communications Applications Conference (SIU)","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/A5066969369","display_name":"Zafer C\u00f6mert","orcid":"https://orcid.org/0000-0001-5256-7648"},"institutions":[{"id":"https://openalex.org/I41055640","display_name":"Bitlis Eren University","ror":"https://ror.org/00mm4ys28","country_code":"TR","type":"education","lineage":["https://openalex.org/I41055640"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Zafer Comert","raw_affiliation_strings":["Computer Engineering, Bitlis Eren University, Bitlis, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Engineering, Bitlis Eren University, Bitlis, Turkey","institution_ids":["https://openalex.org/I41055640"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100354733","display_name":"Yang Zhang","orcid":"https://orcid.org/0000-0002-8540-1254"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang Yang","raw_affiliation_strings":["Communication Engineering, Hangzhou Dianzi University, Zhejiang Sheng, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication Engineering, Hangzhou Dianzi University, Zhejiang Sheng, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003911324","display_name":"Subha Velappan","orcid":"https://orcid.org/0000-0002-4992-4090"},"institutions":[{"id":"https://openalex.org/I182997119","display_name":"Manonmaniam Sundaranar University","ror":"https://ror.org/02qgw5c67","country_code":"IN","type":"education","lineage":["https://openalex.org/I182997119"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Subha Velappan","raw_affiliation_strings":["Computer Science and Engineering, Manonmaniam Sundaranar University, Tamilnadu, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, Manonmaniam Sundaranar University, Tamilnadu, India","institution_ids":["https://openalex.org/I182997119"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064919574","display_name":"A. Manivanna Boopathi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A. Manivanna Boopathi","raw_affiliation_strings":["Electrical and Electronics Engineering, Ariyalur Engineering College, Tamilnadu, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Electronics Engineering, Ariyalur Engineering College, Tamilnadu, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015835206","display_name":"Adnan Fat\u0131h Kocamaz","orcid":"https://orcid.org/0000-0002-7729-8322"},"institutions":[{"id":"https://openalex.org/I41055640","display_name":"Bitlis Eren University","ror":"https://ror.org/00mm4ys28","country_code":"TR","type":"education","lineage":["https://openalex.org/I41055640"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Adnan Fatih Kocamaz","raw_affiliation_strings":["Computer Engineering, Bitlis Eren University, Bitlis, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Engineering, Bitlis Eren University, Bitlis, Turkey","institution_ids":["https://openalex.org/I41055640"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5066969369"],"corresponding_institution_ids":["https://openalex.org/I41055640"],"apc_list":null,"apc_paid":null,"fwci":1.8843,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.87445114,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"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/T11184","display_name":"Neonatal and fetal brain pathology","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/T11184","display_name":"Neonatal and fetal brain pathology","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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":0.9842000007629395,"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"}},{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.982200026512146,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.7663759589195251},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7237181067466736},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7221618890762329},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7129060626029968},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.6881930232048035},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6286378502845764},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6208286285400391},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6070013642311096},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.4914971590042114},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.44648292660713196},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.3647691607475281},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.14370325207710266}],"concepts":[{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.7663759589195251},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7237181067466736},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7221618890762329},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7129060626029968},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.6881930232048035},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6286378502845764},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6208286285400391},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6070013642311096},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.4914971590042114},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.44648292660713196},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.3647691607475281},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.14370325207710266},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu.2018.8404243","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2018.8404243","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1431481846","https://openalex.org/W1965551074","https://openalex.org/W2007221293","https://openalex.org/W2044869919","https://openalex.org/W2117399799","https://openalex.org/W2139212933","https://openalex.org/W2168691138","https://openalex.org/W2171630164","https://openalex.org/W2276759096","https://openalex.org/W2440557406","https://openalex.org/W2469648231","https://openalex.org/W2566250334","https://openalex.org/W2588837640","https://openalex.org/W2732184214","https://openalex.org/W2770971839","https://openalex.org/W2778081019","https://openalex.org/W2790490197","https://openalex.org/W4235285380","https://openalex.org/W6628300050"],"related_works":["https://openalex.org/W2085792030","https://openalex.org/W1588899229","https://openalex.org/W2172291505","https://openalex.org/W2023142747","https://openalex.org/W2037009764","https://openalex.org/W2063036707","https://openalex.org/W2501033992","https://openalex.org/W2377605153","https://openalex.org/W1967182499","https://openalex.org/W2088723847"],"abstract_inverted_index":{"This":[0],"study":[1,78],"proposes":[2],"a":[3,75,92,111],"new":[4],"model":[5,42,50,141],"relying":[6],"on":[7,87],"Empirical":[8],"Mode":[9],"Decomposition":[10],"(EMD)":[11],"and":[12,63,95,115,146],"Discrete":[13],"Wavelet":[14],"Transform":[15],"(DWT)":[16],"in":[17,132],"order":[18],"to":[19,38,79],"detect":[20],"fetal":[21,104],"hypoxia":[22,105],"by":[23],"using":[24,61],"Cardiotocography":[25],"(CTG)":[26],"signals.":[27],"We":[28],"processed":[29],"one":[30],"well":[31],"known":[32],"open":[33],"access":[34],"intrapartum":[35],"CTU-UHB":[36],"database":[37],"find":[39],"if":[40],"our":[41],"could":[43],"outperform":[44],"the":[45,81,119,135,139],"state-of-the":[46],"art":[47],"models.":[48],"The":[49],"consists":[51],"of":[52,83,113,134,144,148],"three":[53],"key":[54],"stages:":[55],"(1)":[56],"Preprocessing,":[57],"(2)":[58],"Features":[59],"extraction":[60,89],"EMD":[62,94,130],"DWT,":[64],"(3)":[65],"Classification":[66],"with":[67],"Support":[68],"Vector":[69],"Machine":[70],"(SVM).":[71],"Also,":[72,107],"we":[73],"present":[74],"comparative":[76],"experimental":[77],"measure":[80],"performance":[82],"SVM":[84,108],"classifier":[85,109],"depending":[86],"feature":[88],"methods.":[90],"As":[91],"result,":[93],"DWT":[96,114,123],"have":[97],"been":[98],"found":[99],"as":[100],"useful":[101],"methods":[102],"for":[103],"detection.":[106],"utilizing":[110],"combination":[112],"morphological":[116],"features":[117,124,131],"achieved":[118],"highest":[120],"performance.":[121],"Furthermore,":[122],"produced":[125],"more":[126],"successful":[127],"results":[128],"than":[129],"terms":[133],"classification":[136],"success.":[137],"Consequently,":[138],"proposed":[140],"ensured":[142],"sensitivity":[143],"57.42%":[145],"specificity":[147],"70.11%.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
