{"id":"https://openalex.org/W3162008471","doi":"https://doi.org/10.1145/3447654.3447665","title":"EEG Signals De-Noising with Wavelet by Optimizing Threshold Based on Fruit Fly Optimization","display_name":"EEG Signals De-Noising with Wavelet by Optimizing Threshold Based on Fruit Fly Optimization","publication_year":2020,"publication_date":"2020-12-18","ids":{"openalex":"https://openalex.org/W3162008471","doi":"https://doi.org/10.1145/3447654.3447665","mag":"3162008471"},"language":"en","primary_location":{"id":"doi:10.1145/3447654.3447665","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3447654.3447665","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3447654.3447665","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 The 9th International Conference on Networks, Communication and Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3447654.3447665","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110928561","display_name":"Xuefei Zhao","orcid":"https://orcid.org/0000-0002-0362-4551"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuefei Zhao","raw_affiliation_strings":["Wuhan University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100407512","display_name":"Dong Liu","orcid":"https://orcid.org/0000-0003-1851-8804"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Liu","raw_affiliation_strings":["Wuhan University of Technology, Wuhan China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology, Wuhan China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026385971","display_name":"Li Ma","orcid":"https://orcid.org/0000-0001-8167-7627"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Ma","raw_affiliation_strings":["Wuhan University of Technology, Wuhan China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology, Wuhan China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091654425","display_name":"Qingsong Ai","orcid":"https://orcid.org/0000-0003-4283-2289"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingsong Ai","raw_affiliation_strings":["Wuhan University of Technology, Wuhan China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology, Wuhan China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114012760","display_name":"Quan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quan Liu","raw_affiliation_strings":["Wuhan University of Technology, Wuhan China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology, Wuhan China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035866142","display_name":"Sheng Quan Xie","orcid":"https://orcid.org/0000-0003-2641-2620"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengquan Xie","raw_affiliation_strings":["Wuhan University of Technology, Wuhan China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology, Wuhan China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5110928561"],"corresponding_institution_ids":["https://openalex.org/I196699116"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.19430599,"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":"71","last_page":"77"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9997000098228455,"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":0.9997000098228455,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6593624949455261},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6050089597702026},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.561394214630127},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5474021434783936},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5463817119598389},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.5264409780502319},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5155324935913086},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.503011167049408},{"id":"https://openalex.org/keywords/matlab","display_name":"MATLAB","score":0.4947454631328583},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4082922041416168},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3917485773563385},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3718852698802948},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36338651180267334},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2565063238143921},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.23004987835884094}],"concepts":[{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6593624949455261},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6050089597702026},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.561394214630127},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5474021434783936},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5463817119598389},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.5264409780502319},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5155324935913086},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.503011167049408},{"id":"https://openalex.org/C2780365114","wikidata":"https://www.wikidata.org/wiki/Q169478","display_name":"MATLAB","level":2,"score":0.4947454631328583},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4082922041416168},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3917485773563385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3718852698802948},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36338651180267334},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2565063238143921},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.23004987835884094},{"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/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","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/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","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},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3447654.3447665","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3447654.3447665","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3447654.3447665","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 The 9th International Conference on Networks, Communication and Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:176186","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Proceedings Paper"}],"best_oa_location":{"id":"doi:10.1145/3447654.3447665","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3447654.3447665","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3447654.3447665","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 The 9th International Conference on Networks, Communication and Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","score":0.5,"display_name":"Life below water"}],"awards":[{"id":"https://openalex.org/G664322881","display_name":null,"funder_award_id":"51675389","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3162008471.pdf","grobid_xml":"https://content.openalex.org/works/W3162008471.grobid-xml"},"referenced_works_count":7,"referenced_works":["https://openalex.org/W2120858734","https://openalex.org/W2129276048","https://openalex.org/W2146842127","https://openalex.org/W2293981118","https://openalex.org/W2893628967","https://openalex.org/W3024649641","https://openalex.org/W3038728753"],"related_works":["https://openalex.org/W4251298892","https://openalex.org/W2356013541","https://openalex.org/W2385444679","https://openalex.org/W3133868776","https://openalex.org/W2382174632","https://openalex.org/W2129959498","https://openalex.org/W2784060934","https://openalex.org/W144391745","https://openalex.org/W4396908843","https://openalex.org/W3109702176"],"abstract_inverted_index":{"EEG":[0,22,148,273],"signal":[1,79],"de-noising":[2],"is":[3,45,80,121,179,205,245],"the":[4,58,75,78,92,104,130,135,172,191,198,215,231,241,272],"preprocessing":[5],"part":[6],"of":[7,30,62,106,137,162,176,202,234],"brain-computer":[8],"interface":[9],"(BCI),":[10],"which":[11],"provides":[12],"a":[13,27,225,279],"relatively":[14],"pure":[15],"source":[16],"for":[17],"controlling":[18],"external":[19],"devices":[20],"with":[21,42,190],"signals.":[23,158],"In":[24,169,195,219,228],"this":[25,267],"paper,":[26],"new":[28],"combination":[29,105],"threshold":[31,33,38,94,96,108],"and":[32,70,74,95,109,112,115,134,150,154,186,210,240,247,256],"function":[34,61,97,133],"based":[35],"on":[36],"wavelet":[37,93,131],"(WT)":[39],"de-nosing":[40],"method":[41,164,178,204,236,264],"undetermined":[43],"coefficients":[44,54],"proposed.":[46],"Using":[47],"fruit":[48],"fly":[49],"optimization":[50,253],"algorithm":[51,254,260],"(FOA),":[52],"these":[53],"are":[55,101,143],"determined":[56,98],"by":[57,99,181],"combined":[59],"fitness":[60],"signal-to-noise":[63],"ratio":[64],"(SNR),":[65],"mean":[66],"square":[67],"error":[68],"(MSE)":[69],"smooth":[71],"factor":[72],"(S),":[73],"noise":[76,89,152],"in":[77,266],"adaptively":[81],"removed.":[82],"Experimental":[83],"results":[84],"show":[85],"that":[86],"under":[87],"different":[88],"addition":[90],"conditions,":[91],"FOA":[100,221],"better":[102,270],"than":[103,214,250],"fixed":[107],"traditional":[110],"hard":[111],"soft":[113],"thresholds,":[114],"other":[116],"improved":[117],"methods.":[118,194,218],"The":[119,159,263],"experiment":[120],"carried":[122],"out":[123],"using":[124],"MATLAB":[125],"simulation":[126],"software.":[127],"According":[128],"to":[129,145,238,277],"basis":[132],"number":[136],"decomposition":[138],"levels,":[139],"two":[140],"experimental":[141],"conditions":[142],"designed":[144],"generate":[146],"simulated":[147],"signals":[149],"add":[151],"respectively,":[153,188],"then":[155],"obtain":[156],"reconstructed":[157],"highest":[160],"SNR":[161,175,201],"our":[163,177,203,235],"can":[165,222,269],"reaches":[166],"18.0297":[167],".":[168],"Condition":[170,196,229],"1,":[171,230],"overall":[173,199,242],"average":[174,200,243],"increased":[180],"27.98%,":[182],"38.29%,":[183],"31.96%":[184],"18.36%":[185],"6.29%,":[187],"compared":[189],"above":[192,216],"comparison":[193],"2,":[197],"23.67%,":[206],"31.13%,":[207],"35.33%,":[208],"12.53%":[209],"7.45%":[211],"respectively":[212],"higher":[213],"same":[217],"addition,":[220],"help":[223],"reconstruct":[224],"smoother":[226],"signal.":[227],"lowest":[232],"S":[233,244],"drops":[237],"0.1735,":[239],"7.86%":[246],"5.80%":[248],"lower":[249],"particle":[251],"swarm":[252,259],"(PSO)":[255],"artificial":[257],"fish":[258],"(AFSA)":[261],"respectively.":[262],"proposed":[265],"paper":[268],"preprocess":[271],"signal,":[274],"so":[275],"as":[276],"achieve":[278],"more":[280],"accurate":[281],"BCI.":[282]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}