{"id":"https://openalex.org/W3198436897","doi":"https://doi.org/10.1109/embc46164.2021.9630588","title":"Multistage Pruning of CNN Based ECG Classifiers for Edge Devices","display_name":"Multistage Pruning of CNN Based ECG Classifiers for Edge Devices","publication_year":2021,"publication_date":"2021-11-01","ids":{"openalex":"https://openalex.org/W3198436897","doi":"https://doi.org/10.1109/embc46164.2021.9630588","mag":"3198436897","pmid":"https://pubmed.ncbi.nlm.nih.gov/34891672"},"language":"en","primary_location":{"id":"doi:10.1109/embc46164.2021.9630588","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc46164.2021.9630588","pdf_url":null,"source":{"id":"https://openalex.org/S4363607750","display_name":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","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/A5100353865","display_name":"Xiaolin Li","orcid":"https://orcid.org/0000-0002-4312-7752"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Li Xiaolin","raw_affiliation_strings":["University College Dublin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College Dublin","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046881927","display_name":"Rajesh C. Panicker","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Rajesh C. Panicker","raw_affiliation_strings":["National University of Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072460590","display_name":"Barry Cardiff","orcid":"https://orcid.org/0000-0003-1303-8115"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Barry Cardiff","raw_affiliation_strings":["University College Dublin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College Dublin","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029098934","display_name":"Deepu John","orcid":"https://orcid.org/0000-0002-6139-1100"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Deepu John","raw_affiliation_strings":["University College Dublin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College Dublin","institution_ids":["https://openalex.org/I100930933"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2021","issue":null,"first_page":"1965","last_page":"1968"},"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/T12495","display_name":"Electrostatic Discharge in Electronics","score":0.9855999946594238,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9768999814987183,"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/pruning","display_name":"Pruning","score":0.8294730186462402},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7230737209320068},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6027582287788391},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5342129468917847},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5098130106925964},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3591250777244568}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.8294730186462402},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7230737209320068},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6027582287788391},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5342129468917847},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5098130106925964},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3591250777244568},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000076251","descriptor_name":"Wearable Electronic Devices","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000076251","descriptor_name":"Wearable Electronic Devices","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000076251","descriptor_name":"Wearable Electronic Devices","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":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001145","descriptor_name":"Arrhythmias, Cardiac","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D001145","descriptor_name":"Arrhythmias, Cardiac","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D001145","descriptor_name":"Arrhythmias, Cardiac","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","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":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc46164.2021.9630588","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc46164.2021.9630588","pdf_url":null,"source":{"id":"https://openalex.org/S4363607750","display_name":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:34891672","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34891672","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":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2095409369","https://openalex.org/W2103308415","https://openalex.org/W2148143831","https://openalex.org/W2736953746","https://openalex.org/W2748902594","https://openalex.org/W2808168148","https://openalex.org/W2896409484","https://openalex.org/W2951569836","https://openalex.org/W2962851801","https://openalex.org/W2963674932","https://openalex.org/W2997300524","https://openalex.org/W3116399583","https://openalex.org/W3128987212","https://openalex.org/W3158231001","https://openalex.org/W3159958343","https://openalex.org/W6755843862"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Using":[0],"smart":[1],"wearable":[2],"devices":[3],"to":[4,30,111,162,169],"monitor":[5],"patients'":[6],"electrocardiogram":[7],"(ECG)":[8],"for":[9,119,143,155],"real-time":[10],"detection":[11],"of":[12,40,60,68,87,141,151],"arrhythmias":[13],"can":[14,80],"significantly":[15],"improve":[16],"healthcare":[17],"outcomes.":[18],"Convolutional":[19],"neural":[20],"network":[21],"(CNN)":[22],"based":[23],"deep":[24],"learning":[25],"has":[26],"been":[27],"used":[28,123],"successfully":[29],"detect":[31],"anomalous":[32],"beats":[33],"in":[34,49,65,74,89,108,179],"ECG.":[35],"However,":[36],"the":[37,85,131,170],"computational":[38],"complexity":[39,83,104],"existing":[41,112,116],"CNN":[42,90,102,117],"models":[43,55],"prohibits":[44],"them":[45],"from":[46],"being":[47],"implemented":[48],"low-powered":[50],"edge":[51,75],"devices.":[52,76],"Usually,":[53],"such":[54],"are":[56],"complex":[57],"with":[58,105,165],"lots":[59],"model":[61,82,103,118],"parameters":[62],"which":[63],"results":[64],"large":[66],"number":[67],"computations,":[69],"memory,":[70],"and":[71,137,153,157],"power":[72],"usage":[73],"Network":[77],"pruning":[78,98,113,164],"techniques":[79],"reduce":[81],"at":[84],"expense":[86],"performance":[88,109],"models.":[91],"This":[92,147],"paper":[93],"presents":[94],"a":[95,125,176],"novel":[96],"multistage":[97],"technique":[99,133],"that":[100],"reduces":[101],"negligible":[106],"loss":[107],"compared":[110,161],"techniques.":[114],"An":[115],"ECG":[120,144],"classification":[121,145],"is":[122,148],"as":[124],"baseline":[126,171],"reference.":[127],"At":[128],"60%":[129],"sparsity,":[130],"proposed":[132],"achieves":[134],"97.7%":[135],"accuracy":[136,156],"an":[138,149],"F1":[139,158],"score":[140],"93.59%":[142],"tasks.":[146],"improvement":[150],"3.3%":[152],"9%":[154],"Score":[159],"respectively,":[160],"traditional":[163],"fine-tuning":[166],"approach.":[167],"Compared":[168],"model,":[172],"we":[173],"also":[174],"achieve":[175],"60.4%":[177],"decrease":[178],"run-time":[180],"complexity.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":8}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}