{"id":"https://openalex.org/W2902731864","doi":"https://doi.org/10.23919/eusipco.2018.8553046","title":"High Frequency Noise Detection and Handling in ECG Signals","display_name":"High Frequency Noise Detection and Handling in ECG Signals","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2902731864","doi":"https://doi.org/10.23919/eusipco.2018.8553046","mag":"2902731864"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2018.8553046","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553046","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","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/A5060918828","display_name":"Kjell Le","orcid":null},"institutions":[{"id":"https://openalex.org/I92008406","display_name":"University of Stavanger","ror":"https://ror.org/02qte9q33","country_code":"NO","type":"education","lineage":["https://openalex.org/I92008406"]}],"countries":["NO"],"is_corresponding":true,"raw_author_name":"Kjell Le","raw_affiliation_strings":["Department of Electrical Engineering and Computer, Science University of Stavanger"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer, Science University of Stavanger","institution_ids":["https://openalex.org/I92008406"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035565080","display_name":"Trygve Eftest\u00f8l","orcid":"https://orcid.org/0000-0003-4487-7018"},"institutions":[{"id":"https://openalex.org/I92008406","display_name":"University of Stavanger","ror":"https://ror.org/02qte9q33","country_code":"NO","type":"education","lineage":["https://openalex.org/I92008406"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Trygve EftestOl","raw_affiliation_strings":["Department of Electrical Engineering and Computer, Science University of Stavanger"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer, Science University of Stavanger","institution_ids":["https://openalex.org/I92008406"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068843545","display_name":"Kjersti Engan","orcid":"https://orcid.org/0000-0002-8970-0067"},"institutions":[{"id":"https://openalex.org/I92008406","display_name":"University of Stavanger","ror":"https://ror.org/02qte9q33","country_code":"NO","type":"education","lineage":["https://openalex.org/I92008406"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Kjersti Engan","raw_affiliation_strings":["Department of Electrical Engineering and Computer, Science University of Stavanger"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer, Science University of Stavanger","institution_ids":["https://openalex.org/I92008406"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045495581","display_name":"Stein \u00d8rn","orcid":"https://orcid.org/0000-0002-5098-4592"},"institutions":[{"id":"https://openalex.org/I92008406","display_name":"University of Stavanger","ror":"https://ror.org/02qte9q33","country_code":"NO","type":"education","lineage":["https://openalex.org/I92008406"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Stein Orn","raw_affiliation_strings":["Department of Electrical Engineering and Computer, Science University of Stavanger"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer, Science University of Stavanger","institution_ids":["https://openalex.org/I92008406"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075345594","display_name":"\u00d8yunn Kleiven","orcid":"https://orcid.org/0000-0002-3316-1295"},"institutions":[{"id":"https://openalex.org/I2800132241","display_name":"Stavanger University Hospital","ror":"https://ror.org/04zn72g03","country_code":"NO","type":"healthcare","lineage":["https://openalex.org/I2800132241"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Oyunn Kleiven","raw_affiliation_strings":["Department of Cardiology, Stavanger University Hospital"],"affiliations":[{"raw_affiliation_string":"Department of Cardiology, Stavanger University Hospital","institution_ids":["https://openalex.org/I2800132241"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5060918828"],"corresponding_institution_ids":["https://openalex.org/I92008406"],"apc_list":null,"apc_paid":null,"fwci":0.5086,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70411157,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"46","last_page":"50"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9915000200271606,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.7954070568084717},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.7131421566009521},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6706236600875854},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.6259622573852539},{"id":"https://openalex.org/keywords/detection-theory","display_name":"Detection theory","score":0.5805854797363281},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5351173877716064},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.5303709506988525},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5215948820114136},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5062324404716492},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4837172329425812},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4512906074523926},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3761734366416931},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.28859376907348633},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.14878234267234802},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1311834454536438}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.7954070568084717},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.7131421566009521},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6706236600875854},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.6259622573852539},{"id":"https://openalex.org/C137270730","wikidata":"https://www.wikidata.org/wiki/Q120811","display_name":"Detection theory","level":3,"score":0.5805854797363281},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5351173877716064},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.5303709506988525},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5215948820114136},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5062324404716492},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4837172329425812},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4512906074523926},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3761734366416931},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.28859376907348633},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.14878234267234802},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1311834454536438},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2018.8553046","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553046","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"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":22,"referenced_works":["https://openalex.org/W1883664232","https://openalex.org/W2007221293","https://openalex.org/W2020271854","https://openalex.org/W2030837440","https://openalex.org/W2038425697","https://openalex.org/W2043365522","https://openalex.org/W2057183507","https://openalex.org/W2065391104","https://openalex.org/W2093512257","https://openalex.org/W2107000047","https://openalex.org/W2125056386","https://openalex.org/W2128129993","https://openalex.org/W2141014056","https://openalex.org/W2157825442","https://openalex.org/W2168126647","https://openalex.org/W2290380888","https://openalex.org/W2316075464","https://openalex.org/W2554431896","https://openalex.org/W2597701414","https://openalex.org/W2610184543","https://openalex.org/W6676004498","https://openalex.org/W6735240385"],"related_works":["https://openalex.org/W111869433","https://openalex.org/W2387156362","https://openalex.org/W2074073404","https://openalex.org/W2036807298","https://openalex.org/W1990370133","https://openalex.org/W4285814784","https://openalex.org/W1965055812","https://openalex.org/W1966535600","https://openalex.org/W2093613770","https://openalex.org/W2072903707"],"abstract_inverted_index":{"After":[0],"acquisition":[1],"of":[2,80,84,105,253,276],"new":[3],"clinical":[4],"electrocardiogram":[5],"(ECG)":[6],"signals":[7],"the":[8,29,45,98,102,106,141,161,207,210,234,239,273,277],"first":[9],"step":[10],"is":[11,40,50,54,71,95,113,182,196,213,226],"often":[12],"to":[13,21,43,58,96,167,185,201,242,260],"preprocess":[14],"and":[15,32,158,233],"have":[16],"a":[17,55,74,81,127,132,137,146,169,197,222,257],"signal":[18,30,47,130],"quality":[19],"assessment":[20],"uncover":[22],"noise.":[23,262],"There":[24],"might":[25],"be":[26,120,165,238,267],"restriction":[27],"on":[28,73,101,140,215,272],"length":[31],"other":[33],"issue":[34],"that":[35],"impose":[36],"limitation":[37],"where":[38],"it":[39,189,195,225],"not":[41],"possible":[42],"discard":[44],"whole":[46],"if":[48],"noise":[49,62,68,99,117,147,172,227,270],"present.":[51],"Thus":[52],"there":[53],"great":[56],"need":[57],"retain":[59],"as":[60,65,131],"much":[61],"free":[63],"regions":[64],"possible.":[66],"A":[67],"detection":[69,148,271],"method":[70],"evaluated":[72],"manually":[75],"annotated":[76],"subset":[77],"(2146":[78],"leads)":[79],"data":[82,107,278],"base":[83,133,142],"12-lead":[85],"ECG":[86,176],"recordings":[87],"from":[88],"1006":[89],"bicycle":[90],"race":[91],"participants.":[92],"The":[93,115,230,246],"aim":[94],"apply":[97],"detector":[100,118,173,259],"unlabelled":[103,274],"part":[104,275],"set":[108],"before":[109],"any":[110],"further":[111],"analysis":[112,181],"conducted.":[114],"proposed":[116],"can":[119],"divided":[121],"into":[122],"3":[123],"parts:":[124],"1)":[125],"Select":[126],"high":[128,170],"frequency":[129,171],"signal.":[134,143],"2)":[135],"Apply":[136],"thresholding":[138],"strategy":[139,232,265],"3)":[144],"Use":[145],"strategy.":[149],"In":[150],"this":[151],"work":[152],"receiver":[153],"operating":[154],"characteristic":[155],"(ROC)":[156],"curve":[157,162,209],"area":[159],"under":[160],"(AUC)":[163],"will":[164,237,266],"used":[166,184,268],"assess":[168,186,202],"designed":[174],"for":[175,269],"signals.":[177],"Even":[178],"though":[179],"ROC":[180,208,244],"widely":[183],"prediction":[187],"models,":[188],"has":[190,221,249],"its":[191],"own":[192],"limitation.":[193],"However,":[194],"good":[198,258],"starting":[199],"point":[200],"discriminatory":[203],"ability.":[204],"To":[205],"generate":[206,243],"performance":[211],"evaluation":[212],"based":[214],"sample-level.":[216],"That":[217],"is,":[218],"each":[219],"sample":[220],"label":[223],"whether":[224],"or":[228],"not.":[229],"threshold":[231,236,264],"chosen":[235],"varying":[240],"factor":[241],"curves.":[245],"best":[247],"model":[248],"an":[250],"average":[251],"AUC":[252],"0.862,":[254],"which":[255],"shows":[256],"discriminate":[261],"This":[263],"set.":[279]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}