{"id":"https://openalex.org/W2791764186","doi":"https://doi.org/10.1109/cisp-bmei.2017.8302146","title":"EEG detection and de-noising based on convolution neural network and Hilbert-Huang transform","display_name":"EEG detection and de-noising based on convolution neural network and Hilbert-Huang transform","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2791764186","doi":"https://doi.org/10.1109/cisp-bmei.2017.8302146","mag":"2791764186"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2017.8302146","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2017.8302146","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5065660222","display_name":"Shuang Wang","orcid":"https://orcid.org/0000-0003-4940-1211"},"institutions":[{"id":"https://openalex.org/I106645853","display_name":"Changchun University of Science and Technology","ror":"https://ror.org/007mntk44","country_code":"CN","type":"education","lineage":["https://openalex.org/I106645853"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuang Wang","raw_affiliation_strings":["Changchun University of Science and Technology, Changchun, China"],"affiliations":[{"raw_affiliation_string":"Changchun University of Science and Technology, Changchun, China","institution_ids":["https://openalex.org/I106645853"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101662203","display_name":"Bin Guo","orcid":"https://orcid.org/0000-0002-9124-1955"},"institutions":[{"id":"https://openalex.org/I106645853","display_name":"Changchun University of Science and Technology","ror":"https://ror.org/007mntk44","country_code":"CN","type":"education","lineage":["https://openalex.org/I106645853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Guo","raw_affiliation_strings":["Changchun University of Science and Technology, Changchun, China"],"affiliations":[{"raw_affiliation_string":"Changchun University of Science and Technology, Changchun, China","institution_ids":["https://openalex.org/I106645853"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103052176","display_name":"Chenjie Zhang","orcid":"https://orcid.org/0009-0006-1493-4383"},"institutions":[{"id":"https://openalex.org/I106645853","display_name":"Changchun University of Science and Technology","ror":"https://ror.org/007mntk44","country_code":"CN","type":"education","lineage":["https://openalex.org/I106645853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenjie Zhang","raw_affiliation_strings":["Changchun University of Science and Technology, Changchun, China"],"affiliations":[{"raw_affiliation_string":"Changchun University of Science and Technology, Changchun, China","institution_ids":["https://openalex.org/I106645853"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032065022","display_name":"Xuemei Bai","orcid":"https://orcid.org/0000-0001-6556-8041"},"institutions":[{"id":"https://openalex.org/I106645853","display_name":"Changchun University of Science and Technology","ror":"https://ror.org/007mntk44","country_code":"CN","type":"education","lineage":["https://openalex.org/I106645853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuemei Bai","raw_affiliation_strings":["Changchun University of Science and Technology, Changchun, China"],"affiliations":[{"raw_affiliation_string":"Changchun University of Science and Technology, Changchun, China","institution_ids":["https://openalex.org/I106645853"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100437368","display_name":"Zhijun Wang","orcid":"https://orcid.org/0009-0003-0835-8736"},"institutions":[{"id":"https://openalex.org/I202028630","display_name":"Changchun Normal University","ror":"https://ror.org/00cbhey71","country_code":"CN","type":"education","lineage":["https://openalex.org/I202028630"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijun Wang","raw_affiliation_strings":["Jilin Engineering Research Center of RFID and Intelligent Information Processing, Changchun Normal University, Changchun, China"],"affiliations":[{"raw_affiliation_string":"Jilin Engineering Research Center of RFID and Intelligent Information Processing, Changchun Normal University, Changchun, China","institution_ids":["https://openalex.org/I202028630"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5065660222"],"corresponding_institution_ids":["https://openalex.org/I106645853"],"apc_list":null,"apc_paid":null,"fwci":0.6408,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.68357122,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"32","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9990000128746033,"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":0.9990000128746033,"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":0.9889000058174133,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9708999991416931,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7204763889312744},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.7059493660926819},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6844706535339355},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6466729044914246},{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.5162570476531982},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.49953222274780273},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4836314916610718},{"id":"https://openalex.org/keywords/hilbert-transform","display_name":"Hilbert transform","score":0.48349836468696594},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.4717184901237488},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.47027021646499634},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4546951353549957},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4427480399608612},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.41724294424057007},{"id":"https://openalex.org/keywords/spectral-density","display_name":"Spectral density","score":0.23466017842292786},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22925636172294617},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1462651789188385}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7204763889312744},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.7059493660926819},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6844706535339355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6466729044914246},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.5162570476531982},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.49953222274780273},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4836314916610718},{"id":"https://openalex.org/C28799612","wikidata":"https://www.wikidata.org/wiki/Q685437","display_name":"Hilbert transform","level":3,"score":0.48349836468696594},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.4717184901237488},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.47027021646499634},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4546951353549957},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4427480399608612},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.41724294424057007},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.23466017842292786},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22925636172294617},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1462651789188385},{"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei.2017.8302146","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2017.8302146","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1968831876","https://openalex.org/W1973863099","https://openalex.org/W1975118665","https://openalex.org/W2007221293","https://openalex.org/W2032197450","https://openalex.org/W2036192142","https://openalex.org/W2160833860","https://openalex.org/W2170077112","https://openalex.org/W2232827647","https://openalex.org/W2243147875","https://openalex.org/W2329020446","https://openalex.org/W2364386214","https://openalex.org/W2570697713","https://openalex.org/W2738456752","https://openalex.org/W6683735938"],"related_works":["https://openalex.org/W2083592477","https://openalex.org/W2363056446","https://openalex.org/W2004948286","https://openalex.org/W2353960620","https://openalex.org/W2107880197","https://openalex.org/W3190676168","https://openalex.org/W2060439639","https://openalex.org/W2074184731","https://openalex.org/W1986719249","https://openalex.org/W1991001811"],"abstract_inverted_index":{"Electroencephalogram(EEG)":[0],"is":[1,27,95,109,121,140,146],"the":[2,36,41,44,66,70,98,105,118,128,135,159],"signal":[3,72,120,145],"fulling":[4],"of":[5,15,43,52,69,137],"randomness":[6],"and":[7,33,55,62],"non-stationarity.":[8],"It's":[9],"very":[10],"susceptible":[11],"by":[12,111,123],"a":[13,50,155],"variety":[14],"noise,":[16],"especially":[17],"electrooculogram":[18],"(EOG).":[19],"In":[20],"order":[21],"to":[22,29,80,88,97,113,126],"reduce":[23],"experimental":[24,131],"errors,":[25],"it":[26],"necessary":[28],"perform":[30],"artifact":[31,53],"recognition":[32],"de-noising":[34],"on":[35,58],"acquired":[37],"original":[38],"signal.":[39],"On":[40],"basis":[42],"traditional":[45],"methods,":[46],"this":[47],"paper":[48],"presents":[49],"method":[51,125,139],"detection":[54],"remove":[56,127],"based":[57],"convolution":[59],"neural":[60],"network(CNN)":[61],"Hilbert-Huang":[63],"transform(HHT).":[64],"Firstly,":[65],"instantaneous":[67],"power":[68],"EEG":[71,99,144],"was":[73,78,86],"calculated.":[74],"The":[75,83,102,130,143],"CNN":[76,138],"model":[77],"used":[79,87],"extract":[81],"features.":[82],"softmax":[84],"classifier":[85],"classify":[89],"EEG.":[90],"Then,":[91],"empirical":[92],"modal":[93],"decomposition":[94],"employed":[96],"with":[100],"artifacts.":[101],"noise":[103],"in":[104],"high":[106],"frequency":[107],"component":[108],"filtered":[110],"referring":[112],"Hilbert":[114],"transform":[115],"spectrum.":[116],"Finally,":[117],"residual":[119],"separated":[122],"FastICA":[124],"EOG.":[129],"results":[132],"show":[133],"that":[134],"accuracy":[136],"over":[141],"80%.":[142],"more":[147],"pure":[148],"after":[149],"HHT":[150],"de-noising.":[151],"This":[152],"work":[153],"lays":[154],"good":[156],"foundation":[157],"for":[158],"follow-up":[160],"study.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
