{"id":"https://openalex.org/W4406457954","doi":"https://doi.org/10.1109/bigdata62323.2024.10825678","title":"Efficient Arrhythmia Detection Using Progressive Resolution Shrinking","display_name":"Efficient Arrhythmia Detection Using Progressive Resolution Shrinking","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406457954","doi":"https://doi.org/10.1109/bigdata62323.2024.10825678"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825678","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5115904456","display_name":"Tavonput Luangphasy","orcid":null},"institutions":[{"id":"https://openalex.org/I137317281","display_name":"Washington State University Vancouver","ror":"https://ror.org/00g2fk805","country_code":"US","type":"education","lineage":["https://openalex.org/I137317281","https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tavonput Luangphasy","raw_affiliation_strings":["Washington State University Vancouver,School of Engineering and Computer Science"],"affiliations":[{"raw_affiliation_string":"Washington State University Vancouver,School of Engineering and Computer Science","institution_ids":["https://openalex.org/I137317281"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007023851","display_name":"Xinghui Zhao","orcid":"https://orcid.org/0000-0002-5120-0972"},"institutions":[{"id":"https://openalex.org/I137317281","display_name":"Washington State University Vancouver","ror":"https://ror.org/00g2fk805","country_code":"US","type":"education","lineage":["https://openalex.org/I137317281","https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinghui Zhao","raw_affiliation_strings":["Washington State University Vancouver,School of Engineering and Computer Science"],"affiliations":[{"raw_affiliation_string":"Washington State University Vancouver,School of Engineering and Computer Science","institution_ids":["https://openalex.org/I137317281"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5115904456"],"corresponding_institution_ids":["https://openalex.org/I137317281"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45966564,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1834","last_page":"1843"},"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.994700014591217,"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"}},{"id":"https://openalex.org/T10217","display_name":"Cardiac electrophysiology and arrhythmias","score":0.9919000267982483,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48884934186935425},{"id":"https://openalex.org/keywords/resizing","display_name":"Resizing","score":0.469954252243042},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.09907898306846619}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48884934186935425},{"id":"https://openalex.org/C56281022","wikidata":"https://www.wikidata.org/wiki/Q11308039","display_name":"Resizing","level":3,"score":0.469954252243042},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.09907898306846619},{"id":"https://openalex.org/C105639569","wikidata":"https://www.wikidata.org/wiki/Q582577","display_name":"Economic policy","level":1,"score":0.0},{"id":"https://openalex.org/C2910001868","wikidata":"https://www.wikidata.org/wiki/Q458","display_name":"European union","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825678","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W125869453","https://openalex.org/W1658008008","https://openalex.org/W1686810756","https://openalex.org/W1900165402","https://openalex.org/W2069724511","https://openalex.org/W2126617656","https://openalex.org/W2133665775","https://openalex.org/W2143257933","https://openalex.org/W2167824641","https://openalex.org/W2167865572","https://openalex.org/W2420085356","https://openalex.org/W2463542070","https://openalex.org/W2483278462","https://openalex.org/W2598842133","https://openalex.org/W2617110182","https://openalex.org/W2776570471","https://openalex.org/W2784094750","https://openalex.org/W2888670469","https://openalex.org/W2927752485","https://openalex.org/W2963263347","https://openalex.org/W3017286598","https://openalex.org/W3097679043","https://openalex.org/W3116277439","https://openalex.org/W3120049641","https://openalex.org/W3122226502","https://openalex.org/W3136882821","https://openalex.org/W3165244048","https://openalex.org/W3184833890","https://openalex.org/W4205528328","https://openalex.org/W4241637638","https://openalex.org/W4295074160","https://openalex.org/W4394841352","https://openalex.org/W6636881020","https://openalex.org/W6637373629","https://openalex.org/W6665319086","https://openalex.org/W6679244116","https://openalex.org/W6726497184","https://openalex.org/W6740609221","https://openalex.org/W6742953368","https://openalex.org/W6750097528","https://openalex.org/W6755455940","https://openalex.org/W6788459886","https://openalex.org/W6922480057"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W246416693","https://openalex.org/W647263804","https://openalex.org/W4200241426","https://openalex.org/W163671557","https://openalex.org/W1579571183","https://openalex.org/W4390595827","https://openalex.org/W2166847561"],"abstract_inverted_index":{"Cardiovascular":[0],"diseases,":[1],"such":[2],"as":[3],"heart":[4,8],"attack":[5],"and":[6,20,51,63,147,169],"congestive":[7],"failure,":[9],"are":[10],"the":[11,17,45,86,96,128,138,144,155,170,178,193],"leading":[12],"cause":[13],"of":[14,88,92,95,119,140,157,180],"death":[15],"in":[16,58,136],"United":[18],"States":[19],"worldwide.":[21],"The":[22],"current":[23],"medical":[24],"practice":[25],"for":[26,33,101,115,123,143,195],"diagnosing":[27],"cardiovascular":[28],"diseases":[29],"is":[30,44,99],"not":[31],"suitable":[32],"long-term,":[34,40],"out-of-hospital":[35],"use.":[36],"A":[37],"key":[38],"to":[39,47,71,75,153],"at-home":[41],"cardiac":[42,54],"care":[43],"ability":[46],"provide":[48],"continuous":[49],"monitoring,":[50],"detect":[52],"abnormal":[53],"rhythms,":[55],"i.e.,":[56],"arrhythmia,":[57],"real-time.":[59],"Various":[60],"big":[61],"data":[62,74],"deep":[64,120],"learning":[65,121,145],"based":[66],"approaches":[67],"have":[68,161],"been":[69],"developed":[70,148],"analyze":[72],"electrocardiogram":[73,167],"identify":[76],"arrhythmia":[77,89,124,181,197],"conditions.":[78],"However,":[79],"most":[80],"existing":[81],"studies":[82],"only":[83],"focus":[84],"on":[85,199],"accuracy":[87],"classification,":[90],"instead":[91],"runtime":[93],"performance":[94],"workflow,":[97],"which":[98],"critical":[100],"real-time":[102,196],"detection.":[103],"In":[104],"this":[105,163,189],"paper,":[106],"we":[107,132],"propose":[108],"progressive":[109],"resolution":[110],"shrinking,":[111],"a":[112,149],"new":[113,150],"method":[114,152],"supporting":[116],"efficient":[117],"execution":[118],"models":[122],"detection,":[125],"without":[126],"compromising":[127],"detection":[129,182,198],"accuracy.":[130,186],"Specifically,":[131],"explored":[133],"multidimensional":[134],"methods":[135],"reducing":[137],"amount":[139],"information":[141],"needed":[142],"task,":[146],"training":[151],"leverage":[154],"advantage":[156],"reduced":[158],"resolution.":[159],"We":[160,187],"evaluated":[162],"approach":[164,190],"using":[165],"real":[166],"data,":[168],"experimental":[171],"results":[172],"show":[173],"that":[174],"it":[175],"effectively":[176],"improves":[177],"efficiency":[179],"while":[183],"preserving":[184],"high":[185],"expect":[188],"will":[191],"pave":[192],"way":[194],"resource-constrained":[200],"wearable":[201],"devices.":[202]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
