{"id":"https://openalex.org/W4377969859","doi":"https://doi.org/10.1109/isqed57927.2023.10129313","title":"A Deep Learning Approach for Ventricular Arrhythmias Classification using Microcontroller","display_name":"A Deep Learning Approach for Ventricular Arrhythmias Classification using Microcontroller","publication_year":2023,"publication_date":"2023-04-05","ids":{"openalex":"https://openalex.org/W4377969859","doi":"https://doi.org/10.1109/isqed57927.2023.10129313"},"language":"en","primary_location":{"id":"doi:10.1109/isqed57927.2023.10129313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isqed57927.2023.10129313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 24th International Symposium on Quality Electronic Design (ISQED)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5092008477","display_name":"Ya-sine Agrignan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ya-sine Agrignan","raw_affiliation_strings":["University of Connecticut"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Connecticut","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070625162","display_name":"Shanglin Zhou","orcid":"https://orcid.org/0000-0002-6409-7716"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shanglin Zhou","raw_affiliation_strings":["University of Connecticut"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Connecticut","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100746166","display_name":"Jun Bai","orcid":"https://orcid.org/0000-0001-6784-4302"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Bai","raw_affiliation_strings":["University of Connecticut"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Connecticut","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009170496","display_name":"Sahidul Islam","orcid":"https://orcid.org/0000-0002-4488-8182"},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sahidul Islam","raw_affiliation_strings":["The University of Texas at San Antonio"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas at San Antonio","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010254642","display_name":"Sheida Nabavi","orcid":"https://orcid.org/0000-0002-5996-1020"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sheida Nabavi","raw_affiliation_strings":["University of Connecticut"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Connecticut","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059911353","display_name":"Mimi Xie","orcid":"https://orcid.org/0000-0003-1973-2909"},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mimi Xie","raw_affiliation_strings":["The University of Texas at San Antonio"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas at San Antonio","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030060072","display_name":"Caiwen Ding","orcid":"https://orcid.org/0000-0003-0891-1231"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Caiwen Ding","raw_affiliation_strings":["University of Connecticut"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Connecticut","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9970999956130981,"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":0.9955999851226807,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/microcontroller","display_name":"Microcontroller","score":0.7136744856834412},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6823595762252808},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.655558705329895},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5959571599960327},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5794010758399963},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.540552020072937},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4539186954498291},{"id":"https://openalex.org/keywords/static-random-access-memory","display_name":"Static random-access memory","score":0.44272804260253906},{"id":"https://openalex.org/keywords/flash-memory","display_name":"Flash memory","score":0.4153112471103668},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.36659175157546997},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3509686589241028},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3265687823295593}],"concepts":[{"id":"https://openalex.org/C173018170","wikidata":"https://www.wikidata.org/wiki/Q165678","display_name":"Microcontroller","level":2,"score":0.7136744856834412},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6823595762252808},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.655558705329895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5959571599960327},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5794010758399963},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.540552020072937},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4539186954498291},{"id":"https://openalex.org/C68043766","wikidata":"https://www.wikidata.org/wiki/Q267416","display_name":"Static random-access memory","level":2,"score":0.44272804260253906},{"id":"https://openalex.org/C2776531357","wikidata":"https://www.wikidata.org/wiki/Q174077","display_name":"Flash memory","level":2,"score":0.4153112471103668},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.36659175157546997},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3509686589241028},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3265687823295593}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isqed57927.2023.10129313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isqed57927.2023.10129313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 24th International Symposium on Quality Electronic Design (ISQED)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1986610100","https://openalex.org/W2518422757","https://openalex.org/W2702116941","https://openalex.org/W3139039641","https://openalex.org/W3190106860","https://openalex.org/W4288421627","https://openalex.org/W4294975435","https://openalex.org/W4297813615","https://openalex.org/W4297848585","https://openalex.org/W6677580257","https://openalex.org/W6791572139"],"related_works":["https://openalex.org/W4316095964","https://openalex.org/W2383001583","https://openalex.org/W3151633427","https://openalex.org/W2131084560","https://openalex.org/W2771395446","https://openalex.org/W2212894501","https://openalex.org/W2793465010","https://openalex.org/W3024050170","https://openalex.org/W3112038843","https://openalex.org/W2376668782"],"abstract_inverted_index":{"Intra-Cardiac":[0],"Electrogram":[1],"(IEGM)":[2],"is":[3,54,218],"widely":[4],"used":[5],"to":[6,14,87],"identify":[7],"life-threatening":[8,42],"ventricular":[9],"arrhythmias":[10],"in":[11,156,165],"medical":[12],"devices":[13],"prevent":[15],"sudden":[16],"cardiac":[17],"death,":[18],"e.g.,":[19],"Implantable":[20],"Cardioverter":[21],"Defibrillator":[22],"(ICD).":[23],"In":[24],"this":[25],"paper,":[26],"we":[27],"present":[28],"and":[29,59,68,89,110,126,162,199],"explore":[30],"the":[31,39,57,91,95,116,119,123,151],"development":[32],"of":[33,41,61,105,118,146,184,193,197,202,214],"a":[34,75,135,140,178,208],"machine":[35],"learning":[36],"approach":[37],"for":[38,98,129],"detection":[40],"Heart":[43],"Arrhythmias":[44],"through":[45],"IEGM":[46],"Data":[47],"from":[48],"an":[49],"ICD":[50],"Device.":[51],"This":[52],"work":[53],"facilitated":[55],"by":[56,150],"design":[58],"analysis":[60,103],"2":[62],"Convolutional":[63],"Neural":[64],"Network":[65],"(CNN),":[66],"1D":[67,136,175],"2D":[69,187,205],"CNNs,":[70],"that":[71],"perform":[72],"inference":[73,99,127],"on":[74],"Low":[76],"Power":[77],"STM":[78],"Nucleo-32":[79],"MCU.":[80],"Multiple":[81],"microcontroller":[82],"software":[83],"platforms":[84],"are":[85],"utilized":[86],"construct":[88],"deploy":[90],"trained":[92],"models":[93],"onto":[94],"MCU":[96,152],"platform":[97],"measurements.":[100],"The":[101,174,186,204],"experimental":[102],"consists":[104],"minimizing":[106],"Average":[107,143],"Inference":[108,144],"time":[109,128],"onboard":[111],"Memory":[112,158],"Occupation":[113],"while":[114],"maximizing":[115],"accuracy":[117],"models.":[120],"We":[121,133],"profile":[122],"memory":[124],"occupation":[125],"different":[130],"CNN":[131,137,176,188,206],"kernels.":[132],"develop":[134],"structure":[138],"with":[139],"26.20":[141],"ms":[142,192],"out":[145],"10":[147],"measurements":[148],"taken":[149],"platform.":[153],"Model":[154,163,189],"Weights":[155],"Flash":[157],"Occupied":[159],"5.99":[160],"KiB":[161,196,201],"Activations":[164],"SRAM":[166],"(Static":[167],"Random":[168],"Access":[169],"Memory)":[170],"measure":[171],"5.00":[172],"KiB.":[173],"achieves":[177,190,207],"F":[179,209],"<inf":[180,210],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[181,211],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">\u03b2</inf>":[182,212],"score":[183,213],"97.8.":[185],"11.00":[191],"inference,":[194],"3.05":[195],"Flash,":[198],"8.09":[200],"SRAM.":[203],"95.15.":[215],"Our":[216],"code":[217],"publicly":[219],"available":[220],"at":[221],"https://github.com/Zhoushanglin100/TinyML-HuskyCSDeepical.":[222]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}