{"id":"https://openalex.org/W4288049625","doi":"https://doi.org/10.1145/3524383.3524435","title":"Brain Wave Recognition Method for Depression in College Students Based on 2D Convolutional Neural Network","display_name":"Brain Wave Recognition Method for Depression in College Students Based on 2D Convolutional Neural Network","publication_year":2022,"publication_date":"2022-02-26","ids":{"openalex":"https://openalex.org/W4288049625","doi":"https://doi.org/10.1145/3524383.3524435"},"language":"en","primary_location":{"id":"doi:10.1145/3524383.3524435","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3524383.3524435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Big Data and Education","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/A5089402840","display_name":"Baiyang Wang","orcid":"https://orcid.org/0000-0002-4418-0715"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Baiyang Wang","raw_affiliation_strings":["Linyi University, China"],"affiliations":[{"raw_affiliation_string":"Linyi University, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100772082","display_name":"Hongyan Fan","orcid":"https://orcid.org/0000-0001-8774-0017"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyan Fan","raw_affiliation_strings":["Linyi University, China"],"affiliations":[{"raw_affiliation_string":"Linyi University, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100457369","display_name":"Meng Li","orcid":"https://orcid.org/0000-0001-5234-3142"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Li","raw_affiliation_strings":["Linyi University, China"],"affiliations":[{"raw_affiliation_string":"Linyi University, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101858654","display_name":"Fuchun Zhang","orcid":"https://orcid.org/0000-0003-0923-4631"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuchun Zhang","raw_affiliation_strings":["Linyi University, China"],"affiliations":[{"raw_affiliation_string":"Linyi University, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015046625","display_name":"Yuelong Ji","orcid":"https://orcid.org/0000-0001-6901-5030"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuelong Ji","raw_affiliation_strings":["Linyi University, China"],"affiliations":[{"raw_affiliation_string":"Linyi University, China","institution_ids":["https://openalex.org/I15823474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5089402840"],"corresponding_institution_ids":["https://openalex.org/I15823474"],"apc_list":null,"apc_paid":null,"fwci":0.2317,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.48629822,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"393","last_page":"398"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9958000183105469,"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":0.9958000183105469,"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":0.9427000284194946,"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/depression","display_name":"Depression (economics)","score":0.7877984046936035},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.7758302688598633},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7586356401443481},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5873244404792786},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5633007884025574},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5122441649436951},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5034040808677673},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48020514845848083},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4454890191555023},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4217774271965027},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4198697805404663},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3543957471847534},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3482995629310608},{"id":"https://openalex.org/keywords/psychiatry","display_name":"Psychiatry","score":0.2278805673122406}],"concepts":[{"id":"https://openalex.org/C2776867660","wikidata":"https://www.wikidata.org/wiki/Q1814941","display_name":"Depression (economics)","level":2,"score":0.7877984046936035},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.7758302688598633},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7586356401443481},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5873244404792786},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5633007884025574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5122441649436951},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5034040808677673},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48020514845848083},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4454890191555023},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4217774271965027},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4198697805404663},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3543957471847534},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3482995629310608},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.2278805673122406},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3524383.3524435","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3524383.3524435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Big Data and Education","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1879995557","https://openalex.org/W1969692299","https://openalex.org/W2090704006","https://openalex.org/W2800428573","https://openalex.org/W2884790510","https://openalex.org/W2904279105","https://openalex.org/W3003417734","https://openalex.org/W3121117531","https://openalex.org/W3170549022"],"related_works":["https://openalex.org/W2922348724","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W2964954556","https://openalex.org/W3029198973","https://openalex.org/W2032664813"],"abstract_inverted_index":{"Depression":[0],"is":[1,23,74,179,219,222],"an":[2,75],"imperceptible":[3],"mental":[4],"disease.":[5],"Most":[6],"patients":[7,151],"who":[8],"have":[9,18],"symptoms":[10],"of":[11,27,30,44,57,69,71,118,121,131,137,140,146,149,228],"depression":[12,70,99,123,150],"do":[13,114],"not":[14],"know":[15],"that":[16,197],"they":[17,49],"suffered":[19],"from":[20],"depression.":[21,58,141],"College":[22,39],"a":[24,92,115],"special":[25],"stage":[26],"the":[28,42,55,67,104,119,122,129,156,169,176,182,186,198,207,213,216,225,229],"formation":[29],"one's":[31],"outlook":[32,36],"on":[33,96],"life,":[34,45],"world":[35],"and":[37,47,64,125,134,164,185,192,206],"values.":[38],"students":[40,73],"face":[41,54],"pressure":[43],"study":[46],"employment,thus":[48],"are":[50,152,159,166,190],"more":[51],"likely":[52],"to":[53,61,78,224],"threat":[56],"So":[59],"how":[60],"quickly,":[62],"efficiently":[63],"conveniently":[65],"diagnose":[66],"degree":[68,120],"college":[72,82],"urgent":[76],"problem":[77,130],"be":[79],"solved":[80,128],"in":[81],"student":[83],"management.":[84],"Aiming":[85],"at":[86],"this":[87,89],"problem,":[88],"paper":[90],"proposes":[91],"neural":[93,171],"network":[94,172],"based":[95],"two-dimensional":[97,162],"convolution":[98],"EEG(Electroencephalogram)":[100],"identification":[101],"method.":[102],"Using":[103],"EEG":[105,188,204],"signals":[106,158,189],"collected":[107,153,157],"by":[108],"only":[109],"three":[110],"electrodes,":[111],"it":[112,126],"can":[113,201,209],"preliminary":[116],"diagnosis":[117,136,139],"patients,":[124],"has":[127],"specialized":[132],"equipment":[133,217],"complicated":[135],"traditional":[138],"First,":[142],"brain":[143],"electrical":[144],"signal":[145],"different":[147],"degrees":[148],";":[154],"Secondly,":[155],"converted":[160],"into":[161,168,181],"images":[163],"then":[165],"input":[167,187],"convolutional":[170],"for":[173],"training;":[174],"Finally,":[175],"trained":[177],"model":[178],"loaded":[180],"detection":[183,230],"device,":[184],"diagnosized":[191],"classified.":[193],"The":[194],"results":[195],"show":[196],"proposed":[199],"method":[200],"effectively":[202],"classify":[203],"signals,":[205],"accuracy":[208],"reach":[210],"98.6%.":[211],"At":[212],"same":[214],"time,":[215],"cost":[218],"small,":[220],"which":[221],"conducive":[223],"wide":[226],"application":[227],"system.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}