{"id":"https://openalex.org/W2594218996","doi":"https://doi.org/10.1109/iwbis.2016.7872897","title":"Generalized learning vector quantization particle swarm optimization (GLVQ-PSO) FPGA implementation for real-time electrocardiogram","display_name":"Generalized learning vector quantization particle swarm optimization (GLVQ-PSO) FPGA implementation for real-time electrocardiogram","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2594218996","doi":"https://doi.org/10.1109/iwbis.2016.7872897","mag":"2594218996"},"language":"en","primary_location":{"id":"doi:10.1109/iwbis.2016.7872897","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwbis.2016.7872897","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Workshop on Big Data and Information Security (IWBIS)","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/A5009658645","display_name":"Yulistiyan Wardhana","orcid":"https://orcid.org/0000-0002-3086-4497"},"institutions":[{"id":"https://openalex.org/I29617571","display_name":"University of Indonesia","ror":"https://ror.org/0116zj450","country_code":"ID","type":"education","lineage":["https://openalex.org/I29617571"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Yulistiyan Wardhana","raw_affiliation_strings":["Faculty of Computer Science, Universtias Indonesia"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science, Universtias Indonesia","institution_ids":["https://openalex.org/I29617571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069933043","display_name":"Wisnu Jatmiko","orcid":"https://orcid.org/0000-0002-0530-7955"},"institutions":[{"id":"https://openalex.org/I29617571","display_name":"University of Indonesia","ror":"https://ror.org/0116zj450","country_code":"ID","type":"education","lineage":["https://openalex.org/I29617571"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Wisnu Jatmiko","raw_affiliation_strings":["Faculty of Computer Science, Universtias Indonesia"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science, Universtias Indonesia","institution_ids":["https://openalex.org/I29617571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037666948","display_name":"Muhammad Febrian Rachmadi","orcid":"https://orcid.org/0000-0003-1672-9149"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"M. Febrian Rachmadi","raw_affiliation_strings":["The University of Edinburgh, Edinburgh, Edinburgh, GB"],"affiliations":[{"raw_affiliation_string":"The University of Edinburgh, Edinburgh, Edinburgh, GB","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5009658645"],"corresponding_institution_ids":["https://openalex.org/I29617571"],"apc_list":null,"apc_paid":null,"fwci":0.2245,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.67063528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"6","issue":null,"first_page":"103","last_page":"108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9997000098228455,"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":0.9997000098228455,"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/T10323","display_name":"Analog and Mixed-Signal Circuit Design","score":0.9955999851226807,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.987500011920929,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/learning-vector-quantization","display_name":"Learning vector quantization","score":0.9074783325195312},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.8270708322525024},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.8076624870300293},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6394933462142944},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6080600619316101},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5184451937675476},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.4981980323791504},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46230995655059814},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3230396509170532},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29927515983581543},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2308984100818634},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.22267934679985046}],"concepts":[{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.9074783325195312},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.8270708322525024},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.8076624870300293},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6394933462142944},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6080600619316101},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5184451937675476},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.4981980323791504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46230995655059814},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3230396509170532},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29927515983581543},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2308984100818634},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.22267934679985046}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iwbis.2016.7872897","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwbis.2016.7872897","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Workshop on Big Data and Information Security (IWBIS)","raw_type":"proceedings-article"},{"id":"mag:3163248200","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=201702239891677231","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1505248337","https://openalex.org/W1528653396","https://openalex.org/W1538172314","https://openalex.org/W1941358101","https://openalex.org/W2023203414","https://openalex.org/W2023745373","https://openalex.org/W2069687170","https://openalex.org/W2092781199","https://openalex.org/W2123749980","https://openalex.org/W2167865572","https://openalex.org/W2289111249","https://openalex.org/W2380669522","https://openalex.org/W2478530123","https://openalex.org/W2769552563","https://openalex.org/W6630074129","https://openalex.org/W6631674648","https://openalex.org/W6678524678","https://openalex.org/W6721401849"],"related_works":["https://openalex.org/W2360214423","https://openalex.org/W2156017042","https://openalex.org/W1647056466","https://openalex.org/W2137852660","https://openalex.org/W2515715595","https://openalex.org/W2513378678","https://openalex.org/W2154143144","https://openalex.org/W2543665684","https://openalex.org/W2151941540","https://openalex.org/W79449126"],"abstract_inverted_index":{"Cardiovascular":[0],"system":[1,15],"is":[2,85,109],"the":[3,23,48,81,99,107,111,122],"most":[4],"important":[5],"part":[6],"of":[7,16,31,42,50,75,98],"human":[8],"body":[9],"which":[10,35,78,94],"has":[11,130],"role":[12],"as":[13],"distribution":[14],"Oxygen":[17],"and":[18,119],"body's":[19],"wastes.":[20],"To":[21],"do":[22],"job,":[24],"there":[25],"are":[26,44],"more":[27],"than":[28,116],"60.000":[29],"miles":[30],"blood":[32,52],"vessels":[33,53],"participated":[34],"can":[36,79,95],"caused":[37,56],"a":[38,65,73,88],"problem":[39],"if":[40],"one":[41],"them":[43],"being":[45],"clogged.":[46],"Unfortunately,":[47],"conditions":[49],"clogged":[51],"or":[54],"diseases":[55],"by":[57],"cardiovascular":[58],"malfunction":[59],"could":[60],"not":[61],"be":[62],"detected":[63],"in":[64,121,134],"plain":[66],"view.":[67],"In":[68],"this":[69],"matter,":[70],"we":[71],"proposed":[72],"design":[74],"wearable":[76],"device":[77,84],"detect":[80],"conditions.":[82],"The":[83],"equipped":[86],"with":[87],"newly":[89],"neural":[90],"network":[91],"algorithm,":[92],"GLVQ-PSO,":[93],"give":[96],"recommendation":[97],"heart":[100],"status":[101],"based":[102],"on":[103],"learned":[104],"data.":[105],"After":[106],"research":[108],"conducted,":[110],"algorithm":[112],"produce":[113],"better":[114],"accuracy":[115],"LVQ,":[117],"GLVQ":[118],"FNGLVQ":[120],"high":[123],"level":[124],"language":[125],"implementation.":[126,137],"Yet,":[127],"GLVQ-PSO":[128],"still":[129],"relatively":[131],"worse":[132],"performance":[133],"its":[135],"FPGA":[136]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}