{"id":"https://openalex.org/W4319309820","doi":"https://doi.org/10.1145/3571532.3571554","title":"CEEMDAN-Wavelet Threshold Denoising Method on sEMG","display_name":"CEEMDAN-Wavelet Threshold Denoising Method on sEMG","publication_year":2022,"publication_date":"2022-10-28","ids":{"openalex":"https://openalex.org/W4319309820","doi":"https://doi.org/10.1145/3571532.3571554"},"language":"en","primary_location":{"id":"doi:10.1145/3571532.3571554","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3571532.3571554","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3571532.3571554","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 11th International Conference on Bioinformatics and Biomedical Science","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3571532.3571554","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032283115","display_name":"Jianwei Fang","orcid":"https://orcid.org/0000-0002-6240-2000"},"institutions":[{"id":"https://openalex.org/I49232843","display_name":"Changchun University","ror":"https://ror.org/02an57k10","country_code":"CN","type":"education","lineage":["https://openalex.org/I49232843"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwei Fang","raw_affiliation_strings":["School, Changchun University, China"],"raw_orcid":"https://orcid.org/0000-0002-6240-2000","affiliations":[{"raw_affiliation_string":"School, Changchun University, China","institution_ids":["https://openalex.org/I49232843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028493740","display_name":"Liye Ren","orcid":"https://orcid.org/0000-0003-0985-681X"},"institutions":[{"id":"https://openalex.org/I49232843","display_name":"Changchun University","ror":"https://ror.org/02an57k10","country_code":"CN","type":"education","lineage":["https://openalex.org/I49232843"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liye Ren","raw_affiliation_strings":["Changchun University, China"],"raw_orcid":"https://orcid.org/0000-0003-0985-681X","affiliations":[{"raw_affiliation_string":"Changchun University, China","institution_ids":["https://openalex.org/I49232843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047091879","display_name":"Junyi Tian","orcid":"https://orcid.org/0000-0003-3952-5456"},"institutions":[{"id":"https://openalex.org/I49232843","display_name":"Changchun University","ror":"https://ror.org/02an57k10","country_code":"CN","type":"education","lineage":["https://openalex.org/I49232843"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyi Tian","raw_affiliation_strings":["Changchun University, China"],"raw_orcid":"https://orcid.org/0000-0003-3952-5456","affiliations":[{"raw_affiliation_string":"Changchun University, China","institution_ids":["https://openalex.org/I49232843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076091311","display_name":"Guisong Li","orcid":"https://orcid.org/0000-0001-6875-7745"},"institutions":[{"id":"https://openalex.org/I49232843","display_name":"Changchun University","ror":"https://ror.org/02an57k10","country_code":"CN","type":"education","lineage":["https://openalex.org/I49232843"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guisong Li","raw_affiliation_strings":["Changchun University, China"],"raw_orcid":"https://orcid.org/0000-0001-6875-7745","affiliations":[{"raw_affiliation_string":"Changchun University, China","institution_ids":["https://openalex.org/I49232843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I49232843"],"apc_list":null,"apc_paid":null,"fwci":0.3321,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56518625,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"105","last_page":"109"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9039999842643738,"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"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9039999842643738,"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":0.8369755744934082},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.8273028135299683},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.7038320302963257},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6668449640274048},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6271995902061462},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5819568037986755},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5568903088569641},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5491735935211182},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.467454731464386},{"id":"https://openalex.org/keywords/step-detection","display_name":"Step detection","score":0.459628701210022},{"id":"https://openalex.org/keywords/video-denoising","display_name":"Video denoising","score":0.454462468624115},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.4528438150882721},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.4444595277309418},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.43521174788475037},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36362016201019287},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3443196415901184},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.21874544024467468},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.21853986382484436},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.04713192582130432}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.8369755744934082},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.8273028135299683},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.7038320302963257},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6668449640274048},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6271995902061462},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5819568037986755},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5568903088569641},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5491735935211182},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.467454731464386},{"id":"https://openalex.org/C293773","wikidata":"https://www.wikidata.org/wiki/Q7608015","display_name":"Step detection","level":3,"score":0.459628701210022},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.454462468624115},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.4528438150882721},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4444595277309418},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.43521174788475037},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36362016201019287},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3443196415901184},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.21874544024467468},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.21853986382484436},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.04713192582130432},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"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/C23431618","wikidata":"https://www.wikidata.org/wiki/Q1404672","display_name":"Multiview Video Coding","level":4,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.0},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"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/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3571532.3571554","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3571532.3571554","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3571532.3571554","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 11th International Conference on Bioinformatics and Biomedical Science","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3571532.3571554","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3571532.3571554","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3571532.3571554","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 11th International Conference on Bioinformatics and Biomedical Science","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7799999713897705,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G3968483186","display_name":null,"funder_award_id":"JJKH20210628KJ","funder_id":"https://openalex.org/F4320326270","funder_display_name":"Education Department of Jilin Province"}],"funders":[{"id":"https://openalex.org/F4320322174","display_name":"People's Government of Jilin Province","ror":"https://ror.org/02fzqav45"},{"id":"https://openalex.org/F4320326270","display_name":"Education Department of Jilin Province","ror":"https://ror.org/05782e512"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4319309820.pdf","grobid_xml":"https://content.openalex.org/works/W4319309820.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2387796150","https://openalex.org/W2139368882","https://openalex.org/W2367199645","https://openalex.org/W2903172302","https://openalex.org/W2348643679","https://openalex.org/W2536049644","https://openalex.org/W2967352418","https://openalex.org/W4362581794","https://openalex.org/W2372414973","https://openalex.org/W1988121823"],"abstract_inverted_index":{"In":[0],"view":[1],"of":[2,13,102],"the":[3,6,24,58,74,99],"fact":[4],"that":[5,31,98],"collected":[7],"sEMG":[8],"signal":[9,48],"contains":[10],"a":[11,29,105],"lot":[12],"noise,":[14],"which":[15],"makes":[16],"it":[17,95],"impossible":[18],"to":[19,45,55],"accurately":[20],"identify":[21],"and":[22,40,50,71,80,83,115],"analyze":[23],"signal,":[25],"this":[26],"paper":[27],"proposes":[28],"method":[30,53],"complete":[32],"ensemble":[33],"empirical":[34],"mode":[35],"decomposition":[36],"with":[37,67],"adaptive":[38],"noise":[39],"wavelet":[41,86],"layered":[42,87,117],"threshold":[43,88,118],"denoising":[44,89,100,106],"achieve":[46],"accurate":[47],"identification":[49],"analysis.":[51],"The":[52],"is":[54,96,108],"first":[56,75],"calculate":[57],"correlation":[59],"coefficient":[60],"after":[61,78,90],"CEEMDAN(Cemplete":[62],"Ensemple":[63],"Empirical":[64],"Mode":[65],"Decomposition":[66],"Adaptive":[68],"Noise)":[69],"decomposition,":[70,79],"then":[72,81,84],"denoise":[73],"three":[76],"IMFs":[77],"reconstruct,":[82],"perform":[85],"reconstruction.":[91],"After":[92],"experimental":[93],"comparison,":[94],"found":[97],"effect":[101],"designing":[103],"such":[104],"algorithm":[107],"better":[109],"than":[110],"other":[111],"different":[112],"global":[113],"thresholds":[114],"separate":[116],"denoising.":[119]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}