{"id":"https://openalex.org/W2896097031","doi":"https://doi.org/10.1109/fuzz-ieee.2018.8491544","title":"Multi-scale Weighted Inherent Fuzzy Entropy for EEG Biomarkers","display_name":"Multi-scale Weighted Inherent Fuzzy Entropy for EEG Biomarkers","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2896097031","doi":"https://doi.org/10.1109/fuzz-ieee.2018.8491544","mag":"2896097031"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2018.8491544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2018.8491544","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","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/A5100340891","display_name":"Min Wang","orcid":"https://orcid.org/0000-0002-1580-6387"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Min Wang","raw_affiliation_strings":["University of New South Wales, School of Engineering and Information Technology, Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"University of New South Wales, School of Engineering and Information Technology, Canberra, Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075234257","display_name":"Jiankun Hu","orcid":"https://orcid.org/0000-0003-0230-1432"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jiankun Hu","raw_affiliation_strings":["University of New South Wales, School of Engineering and Information Technology, Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"University of New South Wales, School of Engineering and Information Technology, Canberra, Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022974795","display_name":"Hussein A. Abbass","orcid":"https://orcid.org/0000-0002-8837-0748"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]},{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hussein A. Abbass","raw_affiliation_strings":["University of New South Wales, School of Engineering and Information Technology, Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"University of New South Wales, School of Engineering and Information Technology, Canberra, Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100340891"],"corresponding_institution_ids":["https://openalex.org/I188329596","https://openalex.org/I31746571"],"apc_list":null,"apc_paid":null,"fwci":0.1234,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.47136984,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"101","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998999834060669,"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":0.9998999834060669,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9937999844551086,"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.9930999875068665,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.7002898454666138},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6584953665733337},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.6095075607299805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5649623870849609},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5159366726875305},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4391133189201355},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4340013861656189},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.4196198582649231},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33184462785720825},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32927629351615906},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3235950469970703},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.09691113233566284}],"concepts":[{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.7002898454666138},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6584953665733337},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.6095075607299805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5649623870849609},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5159366726875305},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4391133189201355},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4340013861656189},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.4196198582649231},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33184462785720825},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32927629351615906},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3235950469970703},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.09691113233566284},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/fuzz-ieee.2018.8491544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2018.8491544","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"},{"id":"pmh:oai:arts.units.it:11368/2939124","is_oa":false,"landing_page_url":"http://hdl.handle.net/11368/2939124","pdf_url":null,"source":{"id":"https://openalex.org/S4306400480","display_name":"ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I142444530","host_organization_name":"University of Trieste","host_organization_lineage":["https://openalex.org/I142444530"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1556131344","https://openalex.org/W1862394037","https://openalex.org/W1991033480","https://openalex.org/W2007221293","https://openalex.org/W2059851411","https://openalex.org/W2063682302","https://openalex.org/W2099033296","https://openalex.org/W2101383962","https://openalex.org/W2101547937","https://openalex.org/W2113957296","https://openalex.org/W2151669316","https://openalex.org/W2162800060","https://openalex.org/W2164104048","https://openalex.org/W2588784603","https://openalex.org/W6633205339","https://openalex.org/W6733782095"],"related_works":["https://openalex.org/W3014107421","https://openalex.org/W2363056446","https://openalex.org/W2081563414","https://openalex.org/W2359718298","https://openalex.org/W2377062149","https://openalex.org/W2076661204","https://openalex.org/W2380939102","https://openalex.org/W154554909","https://openalex.org/W2089603224","https://openalex.org/W2072581623"],"abstract_inverted_index":{"Entropy":[0,74],"has":[1,48],"been":[2],"widely":[3],"investigated":[4],"as":[5,76],"an":[6,77,223],"effective":[7,78],"metric":[8],"to":[9,105],"evaluate":[10],"the":[11,26,30,94,107,116,121,150,159,192,206],"dynamic":[12],"complexity":[13],"of":[14,55,134,136,226],"signals.":[15,127],"EEG":[16,35,79,126,129,185],"is":[17,42,144,165,177,195],"biological":[18],"signals":[19,130,186],"that":[20,205,214],"contain":[21],"rich":[22,31],"complex":[23],"dynamics.":[24],"Transforming":[25],"information":[27,139],"encoded":[28],"in":[29,51,125,141],"dynamics":[32,123],"embedded":[33,140],"within":[34],"into":[36],"appropriate":[37],"biomarkers":[38],"with":[39,167,182,222],"discriminatory":[40,212],"powers":[41],"important":[43],"for":[44,81,120,146,171,198,235,243],"event":[45,83],"detection.":[46,245],"It":[47],"broad":[49],"prospects":[50],"a":[52,66,101,132,210],"wide":[53],"range":[54],"applications":[56],"including":[57],"medical":[58],"diagnosis,":[59],"therapy,":[60],"and":[61,153,179,238],"rehabilitation.":[62],"This":[63],"paper":[64],"proposes":[65],"new":[67],"entropy-based":[68,169,220],"measure,":[69],"Multi-scale":[70],"Weighted":[71],"Inherent":[72,89],"Fuzzy":[73],"(WIFEn),":[75],"biomarker":[80],"improving":[82],"detection":[84,181,197,216],"performance.":[85],"WIFEn":[86,208],"first":[87,175],"extracts":[88],"Mode":[90,96],"Functions":[91],"(IMFs)":[92],"using":[93],"Empirical":[95],"Decomposition":[97],"method,":[98],"then":[99],"uses":[100],"weighted":[102,154],"sum":[103,155],"scheme":[104],"fuse":[106],"fuzzy":[108],"entropy":[109],"metrics":[110,170],"calculated":[111],"on":[112],"each":[113],"IMF.":[114],"Finally,":[115],"multi-scale":[117,207],"variation":[118],"accounts":[119],"multi-timescale":[122],"inherent":[124],"Since":[128],"are":[131],"superposition":[133],"series":[135],"oscillations":[137,143],"where":[138],"these":[142],"useful":[145],"estimating":[147],"signal":[148],"complexity,":[149],"aforementioned":[151],"decomposition,":[152],"procedures":[156],"can":[157],"improve":[158],"estimation":[160],"results.":[161],"The":[162,174,202],"proposed":[163],"method":[164],"tested":[166],"three":[168],"two":[172],"tasks.":[173],"task":[176,194],"eye-open":[178],"eye-closed":[180],"resting":[183],"state":[184],"recorded":[187],"from":[188],"10":[189],"subjects;":[190],"while":[191],"second":[193],"seizure":[196,244],"8":[199],"epilepsy":[200],"patients.":[201],"results":[203],"indicate":[204],"provides":[209],"better":[211],"power":[213],"improves":[215],"performance":[217],"than":[218],"classic":[219],"measures,":[221],"averaged":[224],"improvement":[225],"13.7%":[227],"(":[228],"<i":[229],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[230],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">p</i>":[231],"-value":[232],"<;":[233,241],"0.05)":[234,242],"resting-state":[236],"classification":[237],"5.9%":[239],"(p-value":[240]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2018-10-26T00:00:00"}
