{"id":"https://openalex.org/W3193190111","doi":"https://doi.org/10.1145/3469678.3469683","title":"EEG-Based Depression Recognition Using Intrinsic Time-scale Decomposition and Temporal Convolution Network","display_name":"EEG-Based Depression Recognition Using Intrinsic Time-scale Decomposition and Temporal Convolution Network","publication_year":2021,"publication_date":"2021-07-20","ids":{"openalex":"https://openalex.org/W3193190111","doi":"https://doi.org/10.1145/3469678.3469683","mag":"3193190111"},"language":"en","primary_location":{"id":"doi:10.1145/3469678.3469683","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469678.3469683","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Fifth International Conference on Biological Information and Biomedical Engineering","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100328543","display_name":"Yixin Wang","orcid":"https://orcid.org/0000-0002-7330-801X"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixin Wang","raw_affiliation_strings":["Henan University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan University, China","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101737309","display_name":"Fengrui Liu","orcid":"https://orcid.org/0009-0001-5426-4031"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengrui Liu","raw_affiliation_strings":["Henan University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan University, China","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115591138","display_name":"Lijun Yang","orcid":"https://orcid.org/0000-0002-9233-8871"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lijun Yang","raw_affiliation_strings":["Henan University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan University, China","institution_ids":["https://openalex.org/I173899330"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I173899330"],"apc_list":null,"apc_paid":null,"fwci":2.4944,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.89837858,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"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":1.0,"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":1.0,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9936000108718872,"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":0.9919000267982483,"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/softmax-function","display_name":"Softmax function","score":0.9484055042266846},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7643754482269287},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6560088396072388},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.639159083366394},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6158085465431213},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6056603193283081},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5434593558311462},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4416212737560272},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.33979684114456177},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.32388240098953247},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10417038202285767},{"id":"https://openalex.org/keywords/psychiatry","display_name":"Psychiatry","score":0.06941834092140198}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9484055042266846},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7643754482269287},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6560088396072388},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.639159083366394},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6158085465431213},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6056603193283081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5434593558311462},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4416212737560272},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33979684114456177},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32388240098953247},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10417038202285767},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.06941834092140198},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3469678.3469683","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469678.3469683","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Fifth International Conference on Biological Information and Biomedical Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.6100000143051147,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1985329916","https://openalex.org/W2043705607","https://openalex.org/W2050716480","https://openalex.org/W2068497137","https://openalex.org/W2096125904","https://openalex.org/W2101827712","https://openalex.org/W2140531572","https://openalex.org/W2187089797","https://openalex.org/W2343771112","https://openalex.org/W2788029111","https://openalex.org/W2884790510","https://openalex.org/W2947343305","https://openalex.org/W2969987389","https://openalex.org/W3112420985","https://openalex.org/W6819060087"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W4226420367","https://openalex.org/W2962876041","https://openalex.org/W2899027234","https://openalex.org/W3095506574","https://openalex.org/W3190449293","https://openalex.org/W2964954556","https://openalex.org/W3088721469"],"abstract_inverted_index":{"The":[0],"diagnosis":[1,49],"and":[2,17,27,41,58,85,120,201],"treatment":[3],"of":[4,20,50,97,123,165,182,190],"depression":[5,90,143],"is":[6,42,138,150],"very":[7],"important":[8,35],"since":[9],"it":[10],"brings":[11],"a":[12,77],"heavy":[13],"burden":[14],"to":[15,64,101,106,126,140,221],"family":[16],"society.":[18],"Because":[19],"the":[21,47,81,95,117,128,142,155,161,166,172,178,188,191,198],"high":[22],"sensitivity,":[23],"relatively":[24],"low":[25],"cost,":[26],"convenient":[28],"recording,":[29],"electroencephalogram":[30],"(EEG)":[31],"has":[32],"become":[33],"an":[34,132,218],"tool":[36,220],"for":[37,89,154],"monitoring":[38],"brain":[39],"activity":[40],"gradually":[43],"being":[44],"used":[45,139,216],"in":[46],"auxiliary":[48,219],"mental":[51],"diseases.":[52],"EEG":[53,104],"signals":[54],"are":[55,62,114],"typically":[56],"non-linear":[57],"non-stationary.":[59],"Therefore,":[60],"they":[61],"suitable":[63,153],"be":[65,215],"dealt":[66],"with":[67,226],"by":[68],"time-frequency":[69,82],"analysis":[70,83,212],"technique.":[71],"In":[72],"this":[73],"paper,":[74],"we":[75,93,175,195],"propose":[76],"strategy":[78],"that":[79,197],"combines":[80],"technique":[84],"temporal":[86,134],"convolution":[87,135,148],"network":[88,136,149],"recognition.":[91],"Firstly,":[92],"use":[94],"method":[96],"intrinsic":[98],"time-scale":[99],"decomposition":[100],"decompose":[102],"each":[103],"recording":[105],"several":[107],"components.":[108],"And":[109],"secondly,":[110],"some":[111],"statistical":[112],"indices":[113],"calculated":[115],"from":[116,144],"instantaneous":[118,121],"amplitudes":[119],"frequencies":[122],"these":[124],"components":[125],"form":[127],"feature":[129],"vectors.":[130],"Thirdly,":[131],"improved":[133],"(TCN)":[137],"detect":[141],"normal":[145,202],"controls.":[146],"Temporal":[147],"not":[151],"only":[152],"sequence":[156],"model,":[157],"but":[158],"also":[159],"retains":[160],"parallel":[162],"computing":[163],"characteristics":[164],"convolutional":[167],"neural":[168],"network.":[169],"To":[170],"improve":[171],"model":[173],"performance,":[174],"further":[176],"modify":[177],"original":[179],"softmax":[180],"loss":[181],"TCN":[183],"as":[184,217],"L-softmax.":[185],"Experiments":[186],"show":[187],"effectiveness":[189],"proposed":[192],"model.":[193],"Furthermore,":[194],"find":[196],"depressive":[199],"patients":[200,225],"controls":[203],"shows":[204],"different":[205],"patterns":[206],"through":[207],"functional":[208],"connectivity":[209],"analysis.":[210],"Our":[211],"results":[213],"can":[214],"help":[222],"psychiatrists":[223],"diagnose":[224],"depression.":[227]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2026-08-08T01:25:22.217667","created_date":"2025-10-10T00:00:00"}