{"id":"https://openalex.org/W4292862255","doi":"https://doi.org/10.1109/memea54994.2022.9856544","title":"Electrocardiogram Signal Denoising Based on Multi-Threshold Stationary Wavelet Transform","display_name":"Electrocardiogram Signal Denoising Based on Multi-Threshold Stationary Wavelet Transform","publication_year":2022,"publication_date":"2022-06-22","ids":{"openalex":"https://openalex.org/W4292862255","doi":"https://doi.org/10.1109/memea54994.2022.9856544"},"language":"en","primary_location":{"id":"doi:10.1109/memea54994.2022.9856544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea54994.2022.9856544","pdf_url":null,"source":{"id":"https://openalex.org/S4363605601","display_name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","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":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","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/A5046351515","display_name":"Huyang Peng","orcid":"https://orcid.org/0000-0003-1645-7358"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huyang Peng","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071578712","display_name":"Yongrui Chen","orcid":"https://orcid.org/0000-0002-4618-8403"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongrui Chen","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052752661","display_name":"Donglin Shi","orcid":"https://orcid.org/0000-0002-6620-3156"},"institutions":[{"id":"https://openalex.org/I34155123","display_name":"Hebei University of Science and Technology","ror":"https://ror.org/05h3pkk68","country_code":"CN","type":"education","lineage":["https://openalex.org/I34155123"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Donglin Shi","raw_affiliation_strings":["Modern Educational Technology Center, Hebei Sport University,Shijiazhuang,China","Modern Educational Technology Center, Hebei Sport University, Shijiazhuang, China"],"affiliations":[{"raw_affiliation_string":"Modern Educational Technology Center, Hebei Sport University,Shijiazhuang,China","institution_ids":["https://openalex.org/I34155123"]},{"raw_affiliation_string":"Modern Educational Technology Center, Hebei Sport University, Shijiazhuang, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102198225","display_name":"Fengling Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I34155123","display_name":"Hebei University of Science and Technology","ror":"https://ror.org/05h3pkk68","country_code":"CN","type":"education","lineage":["https://openalex.org/I34155123"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengling Xie","raw_affiliation_strings":["Modern Educational Technology Center, Hebei Sport University,Shijiazhuang,China","Modern Educational Technology Center, Hebei Sport University, Shijiazhuang, China"],"affiliations":[{"raw_affiliation_string":"Modern Educational Technology Center, Hebei Sport University,Shijiazhuang,China","institution_ids":["https://openalex.org/I34155123"]},{"raw_affiliation_string":"Modern Educational Technology Center, Hebei Sport University, Shijiazhuang, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5046351515"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.2984,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.36317568,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":1.0,"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":1.0,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory 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/noise-reduction","display_name":"Noise reduction","score":0.655575692653656},{"id":"https://openalex.org/keywords/qrs-complex","display_name":"QRS complex","score":0.6168479323387146},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6053028702735901},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5763177275657654},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.56505286693573},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5577808618545532},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5428112149238586},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5367812514305115},{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.4901338517665863},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.48660457134246826},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.45719045400619507},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.3920990526676178},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.38683900237083435},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08804848790168762}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.655575692653656},{"id":"https://openalex.org/C111773187","wikidata":"https://www.wikidata.org/wiki/Q1969239","display_name":"QRS complex","level":2,"score":0.6168479323387146},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6053028702735901},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5763177275657654},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.56505286693573},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5577808618545532},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5428112149238586},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5367812514305115},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.4901338517665863},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.48660457134246826},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.45719045400619507},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.3920990526676178},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.38683900237083435},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08804848790168762},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/memea54994.2022.9856544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea54994.2022.9856544","pdf_url":null,"source":{"id":"https://openalex.org/S4363605601","display_name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","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":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G4087976954","display_name":null,"funder_award_id":"2020YFC2006700","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1964173398","https://openalex.org/W1978430949","https://openalex.org/W2010409115","https://openalex.org/W2020867940","https://openalex.org/W2054421446","https://openalex.org/W2074820813","https://openalex.org/W2098816250","https://openalex.org/W2104563593","https://openalex.org/W2116679827","https://openalex.org/W2125927307","https://openalex.org/W2161048570","https://openalex.org/W2218975416","https://openalex.org/W2284460700","https://openalex.org/W2336675008","https://openalex.org/W2346836781","https://openalex.org/W2614711037","https://openalex.org/W2793758734","https://openalex.org/W2902778063","https://openalex.org/W2938737526","https://openalex.org/W2945801048","https://openalex.org/W2971641952","https://openalex.org/W3106865607"],"related_works":["https://openalex.org/W1542224353","https://openalex.org/W1661087619","https://openalex.org/W2116854923","https://openalex.org/W2750730210","https://openalex.org/W2236974868","https://openalex.org/W52840052","https://openalex.org/W4312766348","https://openalex.org/W2133587243","https://openalex.org/W4385545089","https://openalex.org/W4401575680"],"abstract_inverted_index":{"With":[0],"the":[1,10,21,86,90,102,108,131,175,186],"increasing":[2],"risks":[3],"of":[4,24,93,122,130,188],"cardiovascular":[5],"diseases":[6],"(CVDs)":[7],"all":[8],"over":[9],"world,":[11],"electrocardiogram":[12],"(ECG)":[13],"monitoring":[14,165],"has":[15],"become":[16],"an":[17],"important":[18],"means":[19],"for":[20,115,127,146],"timely":[22],"diagnosis":[23],"CVDs.":[25],"However,":[26],"ECG":[27,54,94,99,123,133,164],"signal":[28],"can":[29],"be":[30],"easily":[31],"disturbed":[32],"by":[33,42,140],"noises":[34,52],"such":[35],"as":[36,107],"motion":[37],"artifact":[38],"(MA)":[39],"when":[40,101],"recorded":[41],"wearable":[43,166],"devices":[44],"in":[45,53,162],"our":[46],"daily":[47],"life.":[48],"To":[49],"eliminate":[50],"these":[51],"signal,":[55,134],"a":[56,73,128,141],"denoising":[57],"algorithm":[58,77],"based":[59,78,154],"on":[60,79,155,181],"multi-threshold":[61],"stationary":[62],"wavelet":[63],"transform":[64],"(SWT),":[65],"called":[66],"MT-SWT,":[67],"is":[68,105,138],"proposed.":[69],"We":[70,148],"first":[71],"propose":[72],"QRS":[74,87,182],"complex":[75,88,183],"detection":[76,184],"joint":[80],"threshold":[81],"judgement":[82],"to":[83],"accurately":[84],"separate":[85],"from":[89],"other":[91,152],"waves":[92],"signals.":[95],"Then,":[96],"taking":[97],"historical":[98],"signals":[100,124],"human":[103],"body":[104],"static":[106],"reference":[109],"signals,":[110],"we":[111],"set":[112],"multiple":[113],"thresholds":[114],"different":[116,120,217],"SWT":[117,136],"coefficients":[118],"and":[119,158,204],"parts":[121],"respectively.":[125],"Finally,":[126],"section":[129],"input":[132],"each":[135],"coefficient":[137],"processed":[139],"given":[142],"soft":[143],"thresholding":[144],"function":[145],"denoising.":[147],"compare":[149],"MT-SWT":[150,177,194],"with":[151,174],"algorithms":[153],"MIT-BIH":[156],"datasets,":[157],"also":[159],"implement":[160],"it":[161],"real-world":[163],"devices.":[167],"The":[168],"experimental":[169],"results":[170],"show":[171],"that":[172],"compared":[173],"state-of-the-arts,":[176],"achieves":[178,195],"higher":[179],"accuracy":[180],"under":[185,216],"condition":[187],"low":[189,205],"signal-to-noise":[190],"ratio":[191],"(SNR).":[192],"Moreover,":[193],"high":[196],"SNR":[197,218],"improvement":[198],"(":[199,211],"<tex":[200,212],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[201,213],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$SNR_{imp}$</tex>":[202],")":[203,215],"percent":[206],"root":[207],"mean":[208],"square":[209],"difference":[210],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$PRD$</tex>":[214],"conditions.":[219]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
