{"id":"https://openalex.org/W4283706146","doi":"https://doi.org/10.23919/mipro55190.2022.9803337","title":"On the Benefits of Empirical Mode Decomposition in Spatio-temporal EEG Analysis","display_name":"On the Benefits of Empirical Mode Decomposition in Spatio-temporal EEG Analysis","publication_year":2022,"publication_date":"2022-05-23","ids":{"openalex":"https://openalex.org/W4283706146","doi":"https://doi.org/10.23919/mipro55190.2022.9803337"},"language":"en","primary_location":{"id":"doi:10.23919/mipro55190.2022.9803337","is_oa":false,"landing_page_url":"https://doi.org/10.23919/mipro55190.2022.9803337","pdf_url":null,"source":{"id":"https://openalex.org/S4363605136","display_name":"2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO)","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 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO)","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/A5100379699","display_name":"Zeyu Wang","orcid":"https://orcid.org/0000-0002-8900-7481"},"institutions":[{"id":"https://openalex.org/I140275651","display_name":"University of Pannonia","ror":"https://ror.org/03y5egs41","country_code":"HU","type":"education","lineage":["https://openalex.org/I140275651"]}],"countries":["HU"],"is_corresponding":true,"raw_author_name":"Z. Wang","raw_affiliation_strings":["University of Pannonia,Veszprem,Hungary","University of Pannonia, Veszprem, Hungary"],"affiliations":[{"raw_affiliation_string":"University of Pannonia,Veszprem,Hungary","institution_ids":["https://openalex.org/I140275651"]},{"raw_affiliation_string":"University of Pannonia, Veszprem, Hungary","institution_ids":["https://openalex.org/I140275651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042453994","display_name":"Zsuzsanna Nagy","orcid":"https://orcid.org/0009-0009-5413-7284"},"institutions":[{"id":"https://openalex.org/I101202996","display_name":"Semmelweis University","ror":"https://ror.org/01g9ty582","country_code":"HU","type":"education","lineage":["https://openalex.org/I101202996"]},{"id":"https://openalex.org/I140275651","display_name":"University of Pannonia","ror":"https://ror.org/03y5egs41","country_code":"HU","type":"education","lineage":["https://openalex.org/I140275651"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Z. Nagy","raw_affiliation_strings":["University of Pannonia,Veszprem,Hungary","Semmelweiss University, Budapest, Hungary","University of Pannonia, Veszprem, Hungary"],"affiliations":[{"raw_affiliation_string":"University of Pannonia,Veszprem,Hungary","institution_ids":["https://openalex.org/I140275651"]},{"raw_affiliation_string":"Semmelweiss University, Budapest, Hungary","institution_ids":["https://openalex.org/I101202996"]},{"raw_affiliation_string":"University of Pannonia, Veszprem, Hungary","institution_ids":["https://openalex.org/I140275651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041088501","display_name":"Zolt\u00e1n Juh\u00e1sz","orcid":"https://orcid.org/0000-0003-0677-8588"},"institutions":[{"id":"https://openalex.org/I140275651","display_name":"University of Pannonia","ror":"https://ror.org/03y5egs41","country_code":"HU","type":"education","lineage":["https://openalex.org/I140275651"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Z. Juhasz","raw_affiliation_strings":["University of Pannonia,Veszprem,Hungary","University of Pannonia, Veszprem, Hungary"],"affiliations":[{"raw_affiliation_string":"University of Pannonia,Veszprem,Hungary","institution_ids":["https://openalex.org/I140275651"]},{"raw_affiliation_string":"University of Pannonia, Veszprem, Hungary","institution_ids":["https://openalex.org/I140275651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100379699"],"corresponding_institution_ids":["https://openalex.org/I140275651"],"apc_list":null,"apc_paid":null,"fwci":0.603,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.56983568,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"333","last_page":"338"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9959999918937683,"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":0.9959999918937683,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9821000099182129,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.9095709323883057},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.8279340267181396},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7548855543136597},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6074625849723816},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.5901821255683899},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5723792314529419},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5471372604370117},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4718591868877411},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4699426293373108},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.46020787954330444},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.4551730751991272},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.15476557612419128},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.10468626022338867},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.0647534430027008}],"concepts":[{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.9095709323883057},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.8279340267181396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7548855543136597},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6074625849723816},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.5901821255683899},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5723792314529419},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5471372604370117},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4718591868877411},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4699426293373108},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.46020787954330444},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.4551730751991272},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.15476557612419128},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.10468626022338867},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0647534430027008},{"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/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","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},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/mipro55190.2022.9803337","is_oa":false,"landing_page_url":"https://doi.org/10.23919/mipro55190.2022.9803337","pdf_url":null,"source":{"id":"https://openalex.org/S4363605136","display_name":"2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO)","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 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO)","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":42,"referenced_works":["https://openalex.org/W1579112661","https://openalex.org/W1759573318","https://openalex.org/W1966262416","https://openalex.org/W1967670151","https://openalex.org/W2006733010","https://openalex.org/W2007221293","https://openalex.org/W2009149272","https://openalex.org/W2028497691","https://openalex.org/W2029880728","https://openalex.org/W2030084517","https://openalex.org/W2039347446","https://openalex.org/W2048032753","https://openalex.org/W2054294508","https://openalex.org/W2082000059","https://openalex.org/W2100952904","https://openalex.org/W2105420502","https://openalex.org/W2107558893","https://openalex.org/W2108648583","https://openalex.org/W2114607055","https://openalex.org/W2120390927","https://openalex.org/W2123563890","https://openalex.org/W2123828727","https://openalex.org/W2125056386","https://openalex.org/W2136471501","https://openalex.org/W2152716540","https://openalex.org/W2169064120","https://openalex.org/W2169721303","https://openalex.org/W2170392470","https://openalex.org/W2299397083","https://openalex.org/W2335023513","https://openalex.org/W2335581174","https://openalex.org/W2470404915","https://openalex.org/W2564020593","https://openalex.org/W2618517197","https://openalex.org/W2747122029","https://openalex.org/W2800320181","https://openalex.org/W2897667961","https://openalex.org/W2953247723","https://openalex.org/W2962346662","https://openalex.org/W2987595104","https://openalex.org/W4254591541","https://openalex.org/W6675202628"],"related_works":["https://openalex.org/W2364188284","https://openalex.org/W2080197880","https://openalex.org/W2361368121","https://openalex.org/W116012085","https://openalex.org/W2189003114","https://openalex.org/W2108583803","https://openalex.org/W2361199810","https://openalex.org/W2387231345","https://openalex.org/W2078332635","https://openalex.org/W2360197403"],"abstract_inverted_index":{"Empirical":[0],"mode":[1],"decomposition":[2],"(EMD)":[3],"is":[4],"an":[5],"effective":[6],"tool":[7],"for":[8,25],"the":[9,70,103],"analysis":[10,46,101],"of":[11,72,89],"non-linear":[12],"and":[13,30,36,54,60,74,84,106],"non-stationary":[14],"signals,":[15],"which":[16],"has":[17,40],"been":[18,41],"widely":[19],"used":[20],"in":[21,80,91,99],"various":[22],"application":[23],"fields":[24],"noise":[26],"reduction,":[27],"feature":[28],"extraction":[29],"classification.":[31],"Due":[32],"to":[33,43,47,110],"its":[34,75],"adaptive":[35],"data-driven":[37],"nature,":[38],"it":[39],"introduced":[42],"electroencephalography":[44],"(EEG)":[45],"extract":[48],"more":[49],"accurate":[50],"information":[51],"during":[52],"time-frequency":[53],"phase":[55],"analysis,":[56,83],"multi-channel":[57],"signal":[58],"processing,":[59],"brain":[61],"connectivity":[62],"network":[63],"construction.":[64],"In":[65],"our":[66],"paper":[67],"we":[68,95],"review":[69],"development":[71],"EMD":[73,90,104,113],"variants,":[76],"illustrating":[77],"their":[78],"benefits":[79],"spatiotemporal":[81],"EEG":[82,92,100],"introduce":[85],"some":[86],"practical":[87],"applications":[88],"analysis.":[93],"Finally,":[94],"discuss":[96],"future":[97],"opportunities":[98],"with":[102],"method,":[105],"outline":[107],"parallelization":[108],"strategies":[109],"speed":[111],"up":[112],"processing.":[114]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
