{"id":"https://openalex.org/W2318199321","doi":"https://doi.org/10.1109/embc.2014.6943538","title":"Fast clustering algorithm for large ECG data sets based on CS theory in combination with PCA and K-NN methods","display_name":"Fast clustering algorithm for large ECG data sets based on CS theory in combination with PCA and K-NN methods","publication_year":2014,"publication_date":"2014-08-01","ids":{"openalex":"https://openalex.org/W2318199321","doi":"https://doi.org/10.1109/embc.2014.6943538","mag":"2318199321","pmid":"https://pubmed.ncbi.nlm.nih.gov/25569906"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2014.6943538","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2014.6943538","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"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/A5057895336","display_name":"Mohammadreza Balouchestani","orcid":null},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mohammadreza Balouchestani","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086845888","display_name":"Sridhar Krishnan","orcid":"https://orcid.org/0000-0002-4659-564X"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sridhar Krishnan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I530967"],"apc_list":null,"apc_paid":null,"fwci":5.3376,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.95792208,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2014","issue":null,"first_page":"98","last_page":"101"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9993000030517578,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7340491414070129},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6983784437179565},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.575100302696228},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5414602160453796},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5278819799423218},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5206957459449768},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.5042170286178589},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4642634391784668},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.41009974479675293},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.370286762714386}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7340491414070129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6983784437179565},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.575100302696228},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5414602160453796},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5278819799423218},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5206957459449768},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.5042170286178589},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4642634391784668},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.41009974479675293},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.370286762714386}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019992","descriptor_name":"Databases as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019992","descriptor_name":"Databases as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019992","descriptor_name":"Databases as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D025341","descriptor_name":"Principal Component Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D025341","descriptor_name":"Principal Component Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D025341","descriptor_name":"Principal Component Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D044962","descriptor_name":"Data Compression","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D044962","descriptor_name":"Data Compression","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D044962","descriptor_name":"Data Compression","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc.2014.6943538","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2014.6943538","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","raw_type":"proceedings-article"},{"id":"pmid:25569906","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25569906","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1558367459","https://openalex.org/W1982780561","https://openalex.org/W2029556841","https://openalex.org/W2030984484","https://openalex.org/W2037857866","https://openalex.org/W2063310369","https://openalex.org/W2094750855","https://openalex.org/W2098264400","https://openalex.org/W2112598535","https://openalex.org/W2112839782","https://openalex.org/W2126626103","https://openalex.org/W2128303080","https://openalex.org/W2134207998","https://openalex.org/W2148564640","https://openalex.org/W2150112333","https://openalex.org/W2166152820","https://openalex.org/W2169871401","https://openalex.org/W2492181757","https://openalex.org/W6677038246","https://openalex.org/W6679003729","https://openalex.org/W6681934697"],"related_works":["https://openalex.org/W2579148721","https://openalex.org/W4387893611","https://openalex.org/W2347335694","https://openalex.org/W2091056927","https://openalex.org/W2067407580","https://openalex.org/W4317486777","https://openalex.org/W4389669152","https://openalex.org/W2038514069","https://openalex.org/W1967233468","https://openalex.org/W2009181529"],"abstract_inverted_index":{"Long-term":[0],"recording":[1],"of":[2,19,25,35,50,71,204],"Electrocardiogram":[3],"(ECG)":[4],"signals":[5],"plays":[6],"an":[7,102],"important":[8],"role":[9],"in":[10,38,59,77,162],"health":[11],"care":[12],"systems":[13],"for":[14,31,90,192],"diagnostic":[15],"and":[16,23,54,69,127,142,194,197,207],"treatment":[17],"purposes":[18],"heart":[20],"diseases.":[21],"Clustering":[22],"classification":[24,55,182,190],"collecting":[26],"data":[27,136],"are":[28,148],"essential":[29],"parts":[30],"detecting":[32],"concealed":[33],"information":[34],"P-QRS-T":[36],"waves":[37],"the":[39,135,138,151,186],"long-term":[40,94],"ECG":[41,88,95],"recording.":[42,96],"Currently":[43],"used":[44],"algorithms":[45,178],"do":[46],"have":[47],"their":[48],"share":[49],"drawbacks:":[51],"1)":[52],"clustering":[53,81,105],"cannot":[56],"be":[57],"done":[58],"real":[60],"time;":[61],"2)":[62],"they":[63],"suffer":[64],"from":[65],"huge":[66],"energy":[67],"consumption":[68],"load":[70],"sampling.":[72],"These":[73],"drawbacks":[74],"motivated":[75],"us":[76],"developing":[78],"novel":[79],"optimized":[80],"algorithm":[82,106,157,175,188],"which":[83],"could":[84],"easily":[85],"scan":[86],"large":[87],"datasets":[89],"establishing":[91],"low":[92],"power":[93],"In":[97,184],"this":[98],"paper,":[99],"we":[100],"present":[101],"advanced":[103],"K-means":[104],"based":[107,158],"on":[108,159],"Compressed":[109],"Sensing":[110],"(CS)":[111],"theory":[112],"as":[113],"a":[114,198],"random":[115],"sampling":[116],"procedure.":[117],"Then,":[118],"two":[119],"dimensionality":[120],"reduction":[121],"methods:":[122],"Principal":[123],"Component":[124],"Analysis":[125],"(PCA)":[126],"Linear":[128],"Correlation":[129],"Coefficient":[130],"(LCC)":[131],"followed":[132],"by":[133,179],"sorting":[134],"using":[137],"K-Nearest":[139],"Neighbours":[140],"(K-NN)":[141],"Probabilistic":[143],"Neural":[144],"Network":[145],"(PNN)":[146],"classifiers":[147],"applied":[149],"to":[150],"proposed":[152,174,187],"algorithm.":[153],"We":[154],"show":[155],"our":[156],"PCA":[160],"features":[161],"combination":[163],"with":[164],"K-NN":[165,193],"classifier":[166],"shows":[167],"better":[168],"performance":[169],"than":[170],"other":[171],"methods.":[172],"The":[173],"outperforms":[176],"existing":[177],"increasing":[180],"11%":[181],"accuracy.":[183],"addition,":[185],"illustrates":[189],"accuracy":[191],"PNN":[195],"classifiers,":[196],"Receiver":[199],"Operating":[200],"Characteristics":[201],"(ROC)":[202],"area":[203],"99.98%,":[205],"99.83%,":[206],"99.75%":[208],"respectively.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}