{"id":"https://openalex.org/W7127624914","doi":"https://doi.org/10.48550/arxiv.2602.02776","title":"Verification and Identification in ECG biometric on large-scale","display_name":"Verification and Identification in ECG biometric on large-scale","publication_year":2026,"publication_date":"2026-02-02","ids":{"openalex":"https://openalex.org/W7127624914","doi":"https://doi.org/10.48550/arxiv.2602.02776"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.02776","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.02776","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2602.02776","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125041354","display_name":"Scagnetto Arjuna","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Arjuna, Scagnetto","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5125041354"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9853000044822693,"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":0.9853000044822693,"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/T10217","display_name":"Cardiac electrophysiology and arrhythmias","score":0.0017000000225380063,"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/T11932","display_name":"Wireless Body Area Networks","score":0.0013000000035390258,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.6777999997138977},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5364999771118164},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5216000080108643},{"id":"https://openalex.org/keywords/standardization","display_name":"Standardization","score":0.4433000087738037},{"id":"https://openalex.org/keywords/signature","display_name":"Signature (topology)","score":0.39469999074935913},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.3849000036716461},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.38260000944137573},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3580000102519989}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.694599986076355},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.6777999997138977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5688999891281128},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5364999771118164},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5216000080108643},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4740000069141388},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4636000096797943},{"id":"https://openalex.org/C188087704","wikidata":"https://www.wikidata.org/wiki/Q369577","display_name":"Standardization","level":2,"score":0.4433000087738037},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.39469999074935913},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.38260000944137573},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3580000102519989},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.3513999879360199},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.34290000796318054},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.3310999870300293},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.32350000739097595},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.25519999861717224},{"id":"https://openalex.org/C49895821","wikidata":"https://www.wikidata.org/wiki/Q5227368","display_name":"Data verification","level":2,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.02776","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.02776","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.02776","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.02776","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.47507545351982117}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"work":[1],"studies":[2],"electrocardiogram":[3],"(ECG)":[4],"biometrics":[5],"at":[6,114,149],"large":[7],"scale,":[8],"directly":[9],"addressing":[10],"a":[11,49,58,81,93,106,135,160],"critical":[12],"gap":[13],"in":[14,43],"the":[15,17,154],"literature:":[16],"scarcity":[18],"of":[19],"large-scale":[20,107,166],"evaluations":[21],"with":[22,96,124],"operational":[23],"metrics":[24],"and":[25,31,75,92,100,131,151,164],"protocols":[26],"that":[27,37,157,165,182],"enable":[28],"meaningful":[29],"standardization":[30],"comparison":[32],"across":[33,103,186],"studies.":[34],"We":[35,64],"show":[36,156],"identity":[38],"information":[39],"is":[40,168],"already":[41],"present":[42],"tabular":[44,88],"representations":[45],"(fiducial":[46],"features):":[47],"even":[48],"simple":[50],"MLP-based":[51],"embedding":[52],"network":[53],"yields":[54,129],"non-trivial":[55],"performance,":[56],"establishing":[57],"strong":[59],"baseline":[60],"before":[61],"waveform":[62],"modeling.":[63],"then":[65,76],"adopt":[66],"embedding-based":[67],"deep":[68],"learning":[69],"models":[70],"(ArcFace),":[71],"first":[72],"on":[73,77,140],"features":[74],"ECG":[78,158],"waveforms,":[79,91],"showing":[80],"clear":[82],"performance":[83],"jump":[84],"when":[85],"moving":[86],"from":[87],"inputs":[89],"to":[90,147,170],"further":[94],"gain":[95],"larger":[97],"training":[98],"sets":[99],"consistent":[101],"normalization":[102],"train/val/test.":[104],"On":[105],"test":[108],"set,":[109],"verification":[110],"achieves":[111],"high":[112],"TAR":[113],"strict":[115],"FAR":[116],"thresholds":[117],"(TAR=0.908":[118],"@":[119,122],"FAR=1e-3;":[120],"TAR=0.820":[121],"FAR=1e-4)":[123],"EER=2.53\\%":[125],"(all-vs-all);":[126],"closed-set":[127],"identification":[128],"Rank@1=0.812":[130],"Rank@10=0.910.":[132],"In":[133],"open-set,":[134],"two-stage":[136],"pipeline":[137],"(top-$K$":[138],"shortlist":[139],"embeddings":[141],"+":[142],"re-ranking)":[143],"reaches":[144],"DIR@FAR":[145],"up":[146],"0.976":[148],"FAR=1e-3":[150],"1e-4.":[152],"Overall,":[153],"results":[155],"carries":[159],"measurable":[161],"individual":[162],"signature":[163],"testing":[167],"essential":[169],"obtain":[171],"realistic,":[172],"comparable":[173],"metrics.":[174],"The":[175],"study":[176],"provides":[177],"an":[178],"operationally":[179],"grounded":[180],"benchmark":[181],"helps":[183],"standardize":[184],"evaluation":[185],"protocols.":[187]},"counts_by_year":[],"updated_date":"2026-02-07T06:11:34.122080","created_date":"2026-02-06T00:00:00"}