{"id":"https://openalex.org/W4408355142","doi":"https://doi.org/10.1109/icassp49660.2025.10889014","title":"Neural Variational Mode Decomposition and Its Application for ECG Denoising","display_name":"Neural Variational Mode Decomposition and Its Application for ECG Denoising","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408355142","doi":"https://doi.org/10.1109/icassp49660.2025.10889014"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10889014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889014","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5104013772","display_name":"De-Yan Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"De-Yan Lu","raw_affiliation_strings":["National Taiwan University,Graduate Institute of Communication Engineering,Taipei,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Taiwan University,Graduate Institute of Communication Engineering,Taipei,Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112336533","display_name":"Jian-Jiun Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jian-Jiun Ding","raw_affiliation_strings":["National Taiwan University,Graduate Institute of Communication Engineering,Taipei,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Taiwan University,Graduate Institute of Communication Engineering,Taipei,Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044008055","display_name":"Yu Tsao","orcid":"https://orcid.org/0000-0001-6956-0418"},"institutions":[{"id":"https://openalex.org/I4210086894","display_name":"Research Center for Information Technology Innovation, Academia Sinica","ror":"https://ror.org/000zgvm20","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210086894","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu Tsao","raw_affiliation_strings":["Academic Sinica,Research Center for Information Technology Innovation,Taipei,Taiwan"],"affiliations":[{"raw_affiliation_string":"Academic Sinica,Research Center for Information Technology Innovation,Taipei,Taiwan","institution_ids":["https://openalex.org/I4210086894"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5104013772"],"corresponding_institution_ids":["https://openalex.org/I16733864"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08678577,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.9955999851226807,"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":0.9955999851226807,"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":0.9311000108718872,"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":0.9192000031471252,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.7076647877693176},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.5613207221031189},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5498412847518921},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.5082988142967224},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5013916492462158},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4750490188598633},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42216983437538147},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.34509021043777466},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.059054046869277954}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.7076647877693176},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.5613207221031189},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5498412847518921},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.5082988142967224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5013916492462158},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4750490188598633},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42216983437538147},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34509021043777466},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.059054046869277954},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10889014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889014","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.6800000071525574,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1605211334","https://openalex.org/W1964897957","https://openalex.org/W2000982976","https://openalex.org/W2079492280","https://openalex.org/W2080510952","https://openalex.org/W2088202114","https://openalex.org/W2115340664","https://openalex.org/W2117736816","https://openalex.org/W2345653080","https://openalex.org/W2598248062","https://openalex.org/W2610751394","https://openalex.org/W2728659140","https://openalex.org/W2802780250","https://openalex.org/W2890358421","https://openalex.org/W2945801048","https://openalex.org/W2982385021","https://openalex.org/W3010641886","https://openalex.org/W3070038910","https://openalex.org/W3106865607","https://openalex.org/W3194639106","https://openalex.org/W4234379128","https://openalex.org/W4306148638","https://openalex.org/W4323530236","https://openalex.org/W4361275770","https://openalex.org/W4401954498","https://openalex.org/W6638235754","https://openalex.org/W6638667902","https://openalex.org/W6754124787","https://openalex.org/W6849896277"],"related_works":["https://openalex.org/W2380059383","https://openalex.org/W4224278052","https://openalex.org/W2063679720","https://openalex.org/W2031856784","https://openalex.org/W2018218513","https://openalex.org/W2391251536","https://openalex.org/W2185495545","https://openalex.org/W2075046161","https://openalex.org/W2362198218","https://openalex.org/W2385335131"],"abstract_inverted_index":{"Variational":[0],"mode":[1,98],"decomposition":[2,55,79],"(VMD)":[3],"is":[4],"a":[5,69],"widely":[6],"used":[7],"method":[8,155],"for":[9,101,171],"analyzing":[10],"and":[11,14,34,105,110,117,143,163],"denoising":[12,133],"temporal":[13,102],"non-stationary":[15],"signals.":[16],"Several":[17],"extensions":[18],"of":[19,86,96,130,169],"VMD,":[20],"such":[21],"as":[22],"the":[23,53,82,93,123,128,135,153,158,166],"wavelet":[24],"transform":[25],"with":[26,31,81,139],"VMD":[27,32,74],"(VMD-DWT),":[28],"non-local":[29],"means":[30],"(VMD-NLM),":[33],"their":[35],"combination":[36],"(VMD-DWT-NLM),":[37],"have":[38],"demonstrated":[39],"satisfactory":[40],"performance.":[41],"However,":[42],"these":[43],"VMD-based":[44],"methods":[45],"often":[46],"require":[47],"substantial":[48],"online":[49],"computation":[50],"due":[51],"to":[52],"non-linear":[54],"process,":[56],"especially":[57],"when":[58],"processing":[59],"large":[60],"datasets.":[61],"To":[62],"address":[63],"this":[64,66],"challenge,":[65],"study":[67],"proposes":[68],"novel":[70],"approach":[71],"called":[72],"neural":[73,87],"(NVMD),":[75],"which":[76],"integrates":[77],"VMD\u2019s":[78],"capabilities":[80],"powerful":[83],"feature":[84],"extraction":[85],"networks":[88],"(NN),":[89],"while":[90],"adaptively":[91,164],"selecting":[92],"optimal":[94,167],"number":[95,168],"intrinsic":[97],"functions":[99],"(IMFs)":[100],"signal":[103,132],"analysis":[104],"denoising.":[106,174],"Two":[107],"systems,":[108],"NVMD(A)":[109],"NVMD(P),":[111],"were":[112],"developed,":[113],"incorporating":[114],"autoencoder-based":[115],"NN":[116],"progressive":[118],"NN,":[119],"respectively.":[120],"We":[121],"evaluated":[122],"proposed":[124,154],"NVMD":[125],"framework":[126],"on":[127],"task":[129],"ECG":[131,173],"using":[134],"MIT-BIH":[136],"dataset,":[137],"contaminated":[138],"various":[140],"noise":[141],"types":[142],"different":[144],"signal-to-noise":[145],"ratio":[146],"(SNR)":[147],"levels.":[148],"Experimental":[149],"results":[150],"show":[151],"that":[152],"significantly":[156],"improves":[157],"SNR,":[159],"reduces":[160],"computational":[161],"complexity,":[162],"selects":[165],"IMFs":[170],"effective":[172]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
