{"id":"https://openalex.org/W7147630812","doi":"https://doi.org/10.1109/lascas67804.2026.11457124","title":"Electrocardiogram Synthesis from Photoplethysmogram Signals Through Generative Adversarial Networks","display_name":"Electrocardiogram Synthesis from Photoplethysmogram Signals Through Generative Adversarial Networks","publication_year":2026,"publication_date":"2026-02-24","ids":{"openalex":"https://openalex.org/W7147630812","doi":"https://doi.org/10.1109/lascas67804.2026.11457124"},"language":null,"primary_location":{"id":"doi:10.1109/lascas67804.2026.11457124","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lascas67804.2026.11457124","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 17th Latin America Symposium on Circuits and System (LASCAS)","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/A5020939286","display_name":"Victor Ramon Fran\u00e7a Bezerra de Souza","orcid":"https://orcid.org/0000-0002-2602-4292"},"institutions":[{"id":"https://openalex.org/I71437568","display_name":"Universidade de Pernambuco","ror":"https://ror.org/00gtcbp88","country_code":"BR","type":"education","lineage":["https://openalex.org/I71437568"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Victor Ramon Fran\u00e7a Bezerra de Souza","raw_affiliation_strings":["Universidade de Pernambuco,Recife,Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade de Pernambuco,Recife,Brazil","institution_ids":["https://openalex.org/I71437568"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132568239","display_name":"Lucas Bernardino Cardoso","orcid":null},"institutions":[{"id":"https://openalex.org/I71437568","display_name":"Universidade de Pernambuco","ror":"https://ror.org/00gtcbp88","country_code":"BR","type":"education","lineage":["https://openalex.org/I71437568"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Lucas Bernardino Cardoso","raw_affiliation_strings":["Universidade de Pernambuco,Recife,Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade de Pernambuco,Recife,Brazil","institution_ids":["https://openalex.org/I71437568"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012283902","display_name":"\u00c2ngelo Perkusich","orcid":"https://orcid.org/0000-0002-7377-1258"},"institutions":[{"id":"https://openalex.org/I41455075","display_name":"Universidade Federal de Campina Grande","ror":"https://ror.org/00eftnx64","country_code":"BR","type":"education","lineage":["https://openalex.org/I41455075"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Angelo Perkusich","raw_affiliation_strings":["Universidade Federal de Campina Grande, VIRTUS,Campina Grande,Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal de Campina Grande, VIRTUS,Campina Grande,Brazil","institution_ids":["https://openalex.org/I41455075"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5094023363","display_name":"Gutemberg Gon\u00e7alves Dos Santos J\u00fanior","orcid":null},"institutions":[{"id":"https://openalex.org/I41455075","display_name":"Universidade Federal de Campina Grande","ror":"https://ror.org/00eftnx64","country_code":"BR","type":"education","lineage":["https://openalex.org/I41455075"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Gutemberg Gon\u00e7alves dos Santos J\u00fanior","raw_affiliation_strings":["Universidade Federal de Campina Grande, VIRTUS,Campina Grande,Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal de Campina Grande, VIRTUS,Campina Grande,Brazil","institution_ids":["https://openalex.org/I41455075"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5020939286"],"corresponding_institution_ids":["https://openalex.org/I71437568"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.93048008,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9480999708175659,"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"}},"topics":[{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9480999708175659,"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"}},{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.029400000348687172,"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.004100000020116568,"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/photoplethysmogram","display_name":"Photoplethysmogram","score":0.6313999891281128},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5764999985694885},{"id":"https://openalex.org/keywords/narrowband","display_name":"Narrowband","score":0.5335999727249146},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5210999846458435},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5182999968528748},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5102999806404114},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.48840001225471497},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.45249998569488525}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6708999872207642},{"id":"https://openalex.org/C116390426","wikidata":"https://www.wikidata.org/wiki/Q7187885","display_name":"Photoplethysmogram","level":3,"score":0.6313999891281128},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5764999985694885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5764999985694885},{"id":"https://openalex.org/C2776096036","wikidata":"https://www.wikidata.org/wiki/Q1140483","display_name":"Narrowband","level":2,"score":0.5335999727249146},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5210999846458435},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5182999968528748},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5102999806404114},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.48840001225471497},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.45249998569488525},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4352000057697296},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4246000051498413},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.3677000105381012},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.35409998893737793},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3495999872684479},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.33730000257492065},{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.3093000054359436},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2856999933719635},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.2551000118255615}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lascas67804.2026.11457124","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lascas67804.2026.11457124","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 17th Latin America Symposium on Circuits and System (LASCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7481401562690735}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2021044602","https://openalex.org/W2124106073","https://openalex.org/W2787894218","https://openalex.org/W2962182608","https://openalex.org/W3089350906","https://openalex.org/W3120015513","https://openalex.org/W3213530928","https://openalex.org/W4245260774","https://openalex.org/W4380088535"],"related_works":[],"abstract_inverted_index":{"This":[0,17],"paper":[1],"proposes":[2],"synthesizing":[3],"Electrocardiogram":[4],"(ECG)":[5],"signals":[6,136],"from":[7,134],"Photoplethysmogram":[8],"(PPG)":[9],"recordings":[10],"using":[11],"a":[12,23,38,55,85,97,113],"Generative":[13],"Adversarial":[14],"Network":[15],"(GAN).":[16],"proposal":[18],"integrates":[19],"synchronized":[20],"acquisition":[21,68],"through":[22],"custom":[24],"hardware":[25],"platform,":[26],"an":[27],"explicit":[28],"preprocessing":[29],"pipeline":[30],"for":[31],"narrowband":[32],"and":[33,37,47,61,79,96,108],"broadband":[34],"noise":[35],"suppression,":[36],"GAN":[39],"with":[40,65],"dual-domain":[41],"discriminators":[42],"operating":[43],"in":[44,137],"both":[45],"time":[46],"frequency":[48],"domains.":[49],"The":[50],"model":[51],"was":[52],"trained":[53],"on":[54,122],"combined":[56],"dataset":[57],"comprising":[58],"public":[59],"sources":[60],"real-world":[62],"data":[63],"collected":[64],"the":[66,81,128],"proposed":[67,82],"system.":[69],"Under":[70],"realistic":[71],"experimental":[72],"conditions":[73],"(varying":[74],"heart":[75],"rates,":[76],"activity":[77],"levels,":[78],"noise),":[80],"method":[83],"achieved":[84],"Mean":[86],"Squared":[87],"Error":[88],"(MSE)":[89],"of":[90,130],"<tex":[91,101,114],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[92,102,115],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$0.2780":[93],"\\pm":[94,104],"0.05$</tex>":[95],"Pearson":[98],"correlation":[99],"coefficient":[100],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\rho=0.68":[103],"0.03$</tex>":[105],"between":[106],"real":[107],"synthesized":[109],"ECGs,":[110],"corresponding":[111],"to":[112],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{7":[116],"2.":[117],"2":[118],"\\%}$</tex>":[119],"similarity":[120],"based":[121],"normalized":[123],"MSE.":[124],"These":[125],"results":[126],"demonstrate":[127],"feasibility":[129],"reconstructing":[131],"ECG":[132],"morphology":[133],"PPG":[135],"wearablecompatible":[138],"devices.":[139]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}