{"id":"https://openalex.org/W2076348124","doi":"https://doi.org/10.1109/siu.2014.6830324","title":"ECG classification with emprical mode decomposition denoised by wavelet transform","display_name":"ECG classification with emprical mode decomposition denoised by wavelet transform","publication_year":2014,"publication_date":"2014-04-01","ids":{"openalex":"https://openalex.org/W2076348124","doi":"https://doi.org/10.1109/siu.2014.6830324","mag":"2076348124"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2014.6830324","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2014.6830324","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 22nd 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/A5062463769","display_name":"Omer Faruk Karaaslan","orcid":"https://orcid.org/0000-0003-2492-1798"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Omer Faruk Karaaslan","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik \u00dcniversitesi","[Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc Y\u0131ld\u0131z, Teknik \u00dcniversitesi]"],"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik \u00dcniversitesi","institution_ids":["https://openalex.org/I4101805"]},{"raw_affiliation_string":"[Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc Y\u0131ld\u0131z, Teknik \u00dcniversitesi]","institution_ids":["https://openalex.org/I4101805"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082045666","display_name":"G\u00f6khan Bilgin","orcid":"https://orcid.org/0000-0002-5532-477X"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Gokhan Bilgin","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik \u00dcniversitesi","[Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc Y\u0131ld\u0131z, Teknik \u00dcniversitesi]"],"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik \u00dcniversitesi","institution_ids":["https://openalex.org/I4101805"]},{"raw_affiliation_string":"[Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc Y\u0131ld\u0131z, Teknik \u00dcniversitesi]","institution_ids":["https://openalex.org/I4101805"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5062463769"],"corresponding_institution_ids":["https://openalex.org/I4101805"],"apc_list":null,"apc_paid":null,"fwci":0.1943,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59467996,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"101","issue":null,"first_page":"694","last_page":"697"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9994999766349792,"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":0.9994999766349792,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10876","display_name":"Fault Detection and Control Systems","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.8702216148376465},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7610909938812256},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7228926420211792},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7170830965042114},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6438254117965698},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5895411968231201},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.564687192440033},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5250891447067261},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5101733207702637},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.507188081741333},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.48450157046318054},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.36129873991012573},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2667880058288574},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08916658163070679},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.05842393636703491}],"concepts":[{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.8702216148376465},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7610909938812256},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7228926420211792},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7170830965042114},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6438254117965698},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5895411968231201},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.564687192440033},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5250891447067261},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5101733207702637},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.507188081741333},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.48450157046318054},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.36129873991012573},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2667880058288574},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08916658163070679},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.05842393636703491},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu.2014.6830324","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2014.6830324","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 22nd Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1973706214","https://openalex.org/W1976210447","https://openalex.org/W1997624341","https://openalex.org/W2004629338","https://openalex.org/W2007221293","https://openalex.org/W2024021295","https://openalex.org/W2037295034","https://openalex.org/W2086103076","https://openalex.org/W2126796976","https://openalex.org/W2146254945","https://openalex.org/W2152058025","https://openalex.org/W2162800060","https://openalex.org/W2168216490"],"related_works":["https://openalex.org/W3014107421","https://openalex.org/W2363056446","https://openalex.org/W2081563414","https://openalex.org/W2359718298","https://openalex.org/W2377062149","https://openalex.org/W2380939102","https://openalex.org/W154554909","https://openalex.org/W2072581623","https://openalex.org/W2011248322","https://openalex.org/W2329112433"],"abstract_inverted_index":{"At":[0],"the":[1,67,104,107,131],"diagnosis":[2],"and":[3,9,46,113],"treatment":[4],"phases":[5],"of":[6,44,66,106],"heart":[7],"diseases":[8],"arrhythmia,":[10],"ECG":[11,48],"signals":[12],"provide":[13],"great":[14],"assistance":[15],"to":[16,56,139],"doctors.":[17],"In":[18,73,103],"this":[19,74],"study,":[20],"empirical":[21],"mode":[22,58],"decomposition":[23,38],"(EMD)":[24],"which":[25,61,96,117],"does":[26],"not":[27],"need":[28],"a":[29,98],"special":[30],"constraint":[31],"is":[32,62,97],"utilized":[33],"as":[34],"distinct":[35],"from":[36,120],"classic":[37],"techniques":[39],"for":[40,70],"increasing":[41],"classification":[42,132],"accuracies":[43],"non-stationary":[45],"non-linear":[47],"signals.":[49,141],"Then,":[50],"wavelet":[51],"transform":[52],"has":[53,127],"been":[54,128],"applied":[55],"intrinsic":[57],"functions":[59],"(IMFs)":[60],"obtained":[63,79],"after":[64,85],"application":[65],"EMD":[68],"method":[69],"denoising":[71],"purpose.":[72],"way":[75],"new":[76],"features":[77,88],"are":[78,89,118,124],"with":[80,135],"higher":[81],"discriminative":[82],"properties.":[83],"Right":[84],"that,":[86],"extracted":[87],"classified":[90],"by":[91],"support":[92],"vector":[93],"machines":[94],"(SVMs)":[95],"powerful":[99],"kernel":[100],"based":[101],"classifier.":[102],"evaluation":[105],"proposed":[108,136],"approach,":[109],"St.":[110],"Petersburg":[111],"arrhythmia":[112],"ST-T":[114],"European":[115],"datasets":[116],"acquired":[119],"MIT-BIH":[121],"medical":[122],"repository":[123],"used.":[125],"It":[126],"observed":[129],"that":[130],"performance":[133],"increased":[134],"approach":[137],"compared":[138],"original":[140]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
