{"id":"https://openalex.org/W4414079699","doi":"https://doi.org/10.1109/access.2025.3607039","title":"Conditional GAN-Based ECG Signal Denoising With Skin-Electrode Impedance Modeling","display_name":"Conditional GAN-Based ECG Signal Denoising With Skin-Electrode Impedance Modeling","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414079699","doi":"https://doi.org/10.1109/access.2025.3607039"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3607039","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3607039","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3607039","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070646701","display_name":"B.H. Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Bokyu Kim","raw_affiliation_strings":["Department of Mathematical Data Science, Hanyang University, Ansan, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Data Science, Hanyang University, Ansan, Republic of Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110965261","display_name":"Dohun Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dohun Kim","raw_affiliation_strings":["Department of Mathematical Data Science, Hanyang University, Ansan, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Data Science, Hanyang University, Ansan, Republic of Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108522198","display_name":"W.L. Choi","orcid":null},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Woonsang Choi","raw_affiliation_strings":["Department of Mathematical Data Science, Hanyang University, Ansan, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Data Science, Hanyang University, Ansan, Republic of Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060896706","display_name":"Tae\u2010Heon Yang","orcid":"https://orcid.org/0000-0003-4316-4323"},"institutions":[{"id":"https://openalex.org/I24062138","display_name":"Konkuk University","ror":"https://ror.org/025h1m602","country_code":"KR","type":"education","lineage":["https://openalex.org/I24062138"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Tae-Heon Yang","raw_affiliation_strings":["Department of Mechanical Engineering, Konkuk University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Konkuk University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I24062138"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091803644","display_name":"Gwanghyun Jo","orcid":"https://orcid.org/0000-0002-0635-2897"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gwanghyun Jo","raw_affiliation_strings":["Department of Mathematical Data Science, Hanyang University, Ansan, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Data Science, Hanyang University, Ansan, Republic of Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100337287","display_name":"Young-Min Kim","orcid":"https://orcid.org/0000-0001-7417-5290"},"institutions":[{"id":"https://openalex.org/I4210087584","display_name":"Korea Institute of Oriental Medicine","ror":"https://ror.org/005rpmt10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I2801339556","https://openalex.org/I4210087584","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Young-Min Kim","raw_affiliation_strings":["Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I4210087584"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5070646701"],"corresponding_institution_ids":["https://openalex.org/I4575257"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37198205,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"156917","last_page":"156929"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9532999992370605,"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":0.9532999992370605,"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/discriminator","display_name":"Discriminator","score":0.8274000287055969},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6312000155448914},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5983999967575073},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5964999794960022},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4952999949455261},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.43950000405311584},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.3919999897480011}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.8274000287055969},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.757099986076355},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6312000155448914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6220999956130981},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5983999967575073},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5964999794960022},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4952999949455261},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.43950000405311584},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.3919999897480011},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.3666999936103821},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.34929999709129333},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.31450000405311584},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2791999876499176},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3607039","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3607039","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c7d78cd1894144fe974cc25223190eef","is_oa":true,"landing_page_url":"https://doaj.org/article/c7d78cd1894144fe974cc25223190eef","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 156917-156929 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3607039","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3607039","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1929219515","https://openalex.org/W1983619901","https://openalex.org/W2002816941","https://openalex.org/W2004896487","https://openalex.org/W2055063605","https://openalex.org/W2058401544","https://openalex.org/W2059773165","https://openalex.org/W2095409369","https://openalex.org/W2125927307","https://openalex.org/W2126390573","https://openalex.org/W2160986881","https://openalex.org/W2163621334","https://openalex.org/W2345653080","https://openalex.org/W2517057557","https://openalex.org/W2593414223","https://openalex.org/W2791025763","https://openalex.org/W2806149022","https://openalex.org/W2884754815","https://openalex.org/W2885195348","https://openalex.org/W2902644322","https://openalex.org/W2938737526","https://openalex.org/W2962793481","https://openalex.org/W2963073614","https://openalex.org/W2964539095","https://openalex.org/W2972163396","https://openalex.org/W3003299879","https://openalex.org/W3006822225","https://openalex.org/W3033523981","https://openalex.org/W3046015843","https://openalex.org/W3110800241","https://openalex.org/W3113178943","https://openalex.org/W4224222374","https://openalex.org/W4292851291","https://openalex.org/W4323652738","https://openalex.org/W4376866828","https://openalex.org/W4385245566","https://openalex.org/W4392191369","https://openalex.org/W4400128880"],"related_works":["https://openalex.org/W1967092215","https://openalex.org/W2806725213","https://openalex.org/W2144600858","https://openalex.org/W1987631866","https://openalex.org/W2169180314","https://openalex.org/W2792816408","https://openalex.org/W4224096260","https://openalex.org/W2099199400","https://openalex.org/W2180830352","https://openalex.org/W2472517853"],"abstract_inverted_index":{"ECG":[0,48,76,166,244],"signals":[1],"from":[2],"dry":[3],"electrodes,":[4],"commonly":[5],"used":[6],"in":[7,65,138,202,206],"wearable":[8],"devices,":[9],"are":[10],"vulnerable":[11],"to":[12,15,62,123,132,191],"noise":[13,90,122,127],"due":[14],"high":[16,56],"skin-electrode":[17],"impedance.":[18],"In":[19,111,210],"this":[20],"work,":[21],"we":[22,85,113,213],"propose":[23,214],"a":[24,40,46,125,134,215,221],"denoising":[25,72,200],"method":[26,146,218,236],"based":[27],"on":[28,75],"conditional":[29],"generative":[30],"adversarial":[31,148],"networks,":[32],"where":[33,151],"the":[34,43,66,93,97,152,157,161,164,169,204,207,229,234],"noisy":[35,230],"signal":[36,159],"is":[37,60,190],"treated":[38],"as":[39,220],"condition":[41],"for":[42,241],"generation":[44],"of":[45,96,103,163,223],"clean":[47,165],"signal.":[49],"To":[50,82],"develop":[51],"deep":[52],"learning":[53],"models":[54],"with":[55,136],"generalization":[57],"capability,":[58],"it":[59],"important":[61],"ensure":[63],"diversity":[64,137],"training":[67],"dataset.":[68],"However,":[69],"most":[70],"existing":[71],"methods":[73],"rely":[74],"data":[77],"collected":[78],"by":[79],"wet-contact":[80],"electrodes.":[81],"remedy":[83],"this,":[84],"adopt":[86],"an":[87,184],"input-referred":[88],"voltage":[89],"model":[91],"at":[92],"circuit":[94],"level":[95],"measurement":[98],"device,":[99],"incorporating":[100],"three":[101],"types":[102],"internal":[104],"noise:":[105],"amplifier,":[106],"thermal,":[107],"and":[108,119,141,183,231],"flicker":[109],"noise.":[110],"addition,":[112],"include":[114],"baseline":[115],"wander,":[116],"muscle":[117],"artifact,":[118],"electrode":[120],"motion":[121],"construct":[124],"comprehensive":[126],"set.":[128],"This":[129],"allows":[130],"us":[131],"synthesize":[133],"dataset":[135],"both":[139,228],"high-":[140],"low-frequency":[142],"components.":[143],"The":[144],"proposed":[145,235],"employs":[147],"loss":[149,175],"framework":[150],"discriminator":[153],"network":[154,171],"determines":[155],"whether":[156],"denoised":[158,232],"follows":[160],"distribution":[162],"signals.":[167,245],"Meanwhile,":[168],"generator":[170],"minimizes":[172],"additional":[173],"two":[174],"components,":[176],"namely":[177],"<italic":[178],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[179,181],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">L</i><sub":[180],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[182],"identity":[185],"type":[186],"loss,":[187],"whose":[188],"role":[189],"preserve":[192],"noise-free":[193],"segments":[194],"during":[195],"denoisng":[196],"process.We":[197],"observe":[198],"robust":[199],"results":[201,208],"all":[203],"examples":[205],"section.":[209],"one":[211],"example,":[212],"new":[216],"classification":[217,239],"derived":[219],"byproduct":[222],"our":[224],"work.":[225],"By":[226],"leveraging":[227],"signals,":[233],"achieves":[237],"improved":[238],"accuracy":[240],"detecting":[242],"abnormal":[243]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}