{"id":"https://openalex.org/W2532460652","doi":"https://doi.org/10.1109/embc.2016.7590822","title":"EEG-based driver fatigue detection using hybrid deep generic model","display_name":"EEG-based driver fatigue detection using hybrid deep generic model","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2532460652","doi":"https://doi.org/10.1109/embc.2016.7590822","mag":"2532460652","pmid":"https://pubmed.ncbi.nlm.nih.gov/28268447"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2016.7590822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2016.7590822","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://opus.lib.uts.edu.au/bitstream/10453/50472/3/27138FCD-1DB4-4C84-9FBA-23D9D00CBC2D%20am.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048555499","display_name":"Phyo Phyo San","orcid":null},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Phyo Phyo San","raw_affiliation_strings":["Data Analytic Department, Institute for Infocomm Research, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Analytic Department, Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079852457","display_name":"Sai Ho Ling","orcid":"https://orcid.org/0000-0003-0849-5098"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sai Ho Ling","raw_affiliation_strings":["Faculty of Engineering and IT, University of Technology, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and IT, University of Technology, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018877662","display_name":"Rifai Chai","orcid":"https://orcid.org/0000-0002-1922-7024"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Rifai Chai","raw_affiliation_strings":["Faculty of Engineering and IT, University of Technology, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and IT, University of Technology, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040544025","display_name":"Yvonne Tran","orcid":"https://orcid.org/0000-0002-1741-4205"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]},{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yvonne Tran","raw_affiliation_strings":["Faculty of Engineering and IT, University of Technology, Sydney, Australia","Rehabilitation Studies Unit, The University of Sydney, NSW, Australa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and IT, University of Technology, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]},{"raw_affiliation_string":"Rehabilitation Studies Unit, The University of Sydney, NSW, Australa","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051531420","display_name":"Ashley Craig","orcid":"https://orcid.org/0000-0001-7647-7604"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ashley Craig","raw_affiliation_strings":["Rehabilitation Studies Unit, The University of Sydney, NSW, Australa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rehabilitation Studies Unit, The University of Sydney, NSW, Australa","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100716476","display_name":"Hung T. Nguyen","orcid":"https://orcid.org/0000-0003-3373-8178"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hung Nguyen","raw_affiliation_strings":["Faculty of Engineering and IT, University of Technology, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and IT, University of Technology, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.1974,"has_fulltext":true,"cited_by_count":37,"citation_normalized_percentile":{"value":0.93524371,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"2016","issue":null,"first_page":"800","last_page":"803"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9894000291824341,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.973800003528595,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/support-vector-machine","display_name":"Support vector machine","score":0.8685557842254639},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.717132031917572},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6871361136436462},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6757804155349731},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6560342311859131},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.568005383014679},{"id":"https://openalex.org/keywords/decision-boundary","display_name":"Decision boundary","score":0.492180734872818},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.48387014865875244},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.47237280011177063},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4265371263027191},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42612943053245544},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07837387919425964}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8685557842254639},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.717132031917572},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6871361136436462},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6757804155349731},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6560342311859131},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.568005383014679},{"id":"https://openalex.org/C42023084","wikidata":"https://www.wikidata.org/wiki/Q5249231","display_name":"Decision boundary","level":3,"score":0.492180734872818},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.48387014865875244},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.47237280011177063},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4265371263027191},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42612943053245544},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07837387919425964},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000063","descriptor_name":"Accidents, Traffic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000063","descriptor_name":"Accidents, Traffic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000063","descriptor_name":"Accidents, Traffic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D005221","descriptor_name":"Fatigue","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D005221","descriptor_name":"Fatigue","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D005221","descriptor_name":"Fatigue","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008962","descriptor_name":"Models, Theoretical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008962","descriptor_name":"Models, Theoretical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008962","descriptor_name":"Models, Theoretical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1109/embc.2016.7590822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2016.7590822","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:28268447","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28268447","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/50472","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/50472","pdf_url":"https://opus.lib.uts.edu.au/bitstream/10453/50472/3/27138FCD-1DB4-4C84-9FBA-23D9D00CBC2D%20am.pdf","source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"},{"id":"pmh:oai:researchbank.swinburne.edu.au:b31faf43-8514-4376-892d-dcbfa6a523ea/1","is_oa":false,"landing_page_url":"http://hdl.handle.net/1959.3/440633","pdf_url":null,"source":{"id":"https://openalex.org/S4306401157","display_name":"Swinburne Research Bank (Swinburne University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I57093077","host_organization_name":"Swinburne University of Technology","host_organization_lineage":["https://openalex.org/I57093077"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2016), Orlando, Florida, United States, 16-20 August 2016, Vol. 2016-October, pp. 800-803","raw_type":""}],"best_oa_location":{"id":"pmh:oai:opus.lib.uts.edu.au:10453/50472","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/50472","pdf_url":"https://opus.lib.uts.edu.au/bitstream/10453/50472/3/27138FCD-1DB4-4C84-9FBA-23D9D00CBC2D%20am.pdf","source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"},"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2532460652.pdf","grobid_xml":"https://content.openalex.org/works/W2532460652.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W1556947891","https://openalex.org/W1644997609","https://openalex.org/W1964812476","https://openalex.org/W2027856458","https://openalex.org/W2043133488","https://openalex.org/W2050383794","https://openalex.org/W2054237600","https://openalex.org/W2079167592","https://openalex.org/W2085986654","https://openalex.org/W2103184652","https://openalex.org/W2112504244","https://openalex.org/W2117100955","https://openalex.org/W2124537004","https://openalex.org/W2130325614","https://openalex.org/W2136922672","https://openalex.org/W2202505358","https://openalex.org/W2205887246","https://openalex.org/W4205709116","https://openalex.org/W6677004514","https://openalex.org/W6687901878"],"related_works":["https://openalex.org/W2922348724","https://openalex.org/W2130428257","https://openalex.org/W200322357","https://openalex.org/W4308951944","https://openalex.org/W2988848585","https://openalex.org/W4312960290","https://openalex.org/W184442817","https://openalex.org/W2009611918","https://openalex.org/W2032664813","https://openalex.org/W2814966788"],"abstract_inverted_index":{"Classification":[0],"of":[1,7,20,50,146,171],"electroencephalography":[2],"(EEG)-based":[3],"application":[4],"is":[5,16,45,60,69,91,164],"one":[6],"the":[8,82,118,135,159,169],"important":[9],"process":[10],"for":[11,47,73,168],"biomedical":[12],"engineering.":[13],"Driver":[14],"fatigue":[15,139,173],"a":[17,27,36,54],"major":[18],"case":[19],"traffic":[21],"accidents":[22],"worldwide":[23],"and":[24,114,122,128,153],"considered":[25],"as":[26],"significant":[28],"problem":[29],"in":[30,81,125,174],"recent":[31],"decades.":[32],"In":[33,157],"this":[34],"paper,":[35],"hybrid":[37,161],"deep":[38,58],"generic":[39],"model":[40],"(DGM)-based":[41],"support":[42],"vector":[43],"machine":[44],"proposed":[46,136,160],"accurate":[48],"detection":[49,170],"driver":[51,138,172],"fatigue.":[52],"Traditionally,":[53],"probabilistic":[55],"DGM":[56,113],"with":[57,149],"architecture":[59],"quite":[61],"good":[62,99],"at":[63],"learning":[64],"invariant":[65],"features,":[66],"but":[67,97],"it":[68],"not":[70],"always":[71],"optimal":[72],"classification":[74,116],"due":[75],"to":[76,93,104],"its":[77],"trainable":[78],"parameters":[79],"are":[80],"middle":[83],"layer.":[84],"Alternatively,":[85],"Support":[86],"Vector":[87],"Machine":[88],"(SVM)":[89],"itself":[90],"unable":[92],"learn":[94],"complicated":[95],"invariance,":[96],"produces":[98],"decision":[100],"surface":[101],"when":[102],"applied":[103],"well-behaved":[105],"features.":[106],"Consolidating":[107],"unsupervised":[108],"high-level":[109],"feature":[110,126],"extraction":[111,127],"techniques,":[112],"SVM":[115,163],"makes":[117],"integrated":[119],"framework":[120],"stronger":[121],"enhance":[123],"mutually":[124],"classification.":[129],"The":[130],"experimental":[131],"results":[132],"showed":[133],"that":[134],"DBN-based":[137],"monitoring":[140],"system":[141],"achieves":[142],"better":[143],"testing":[144],"accuracy":[145],"73.29":[147],"%":[148,151,155],"91.10":[150],"sensitivity":[152],"55.48":[154],"specificity.":[156],"short,":[158],"DGM-based":[162],"an":[165],"effective":[166],"method":[167],"EEG.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":6}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}