{"id":"https://openalex.org/W3127629071","doi":"https://doi.org/10.1109/bibm49941.2020.9313163","title":"Anomaly Detection on Electroencephalography with Self-supervised Learning","display_name":"Anomaly Detection on Electroencephalography with Self-supervised Learning","publication_year":2020,"publication_date":"2020-12-16","ids":{"openalex":"https://openalex.org/W3127629071","doi":"https://doi.org/10.1109/bibm49941.2020.9313163","mag":"3127629071"},"language":"en","primary_location":{"id":"doi:10.1109/bibm49941.2020.9313163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm49941.2020.9313163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5103022202","display_name":"Junjie Xu","orcid":"https://orcid.org/0000-0003-4892-6390"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Xu","raw_affiliation_strings":["Sun Yat-sen University,School of Data and Computer Science,Guangzhou,China","School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Data and Computer Science,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023488673","display_name":"Yaojia Zheng","orcid":"https://orcid.org/0000-0002-8386-9988"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaojia Zheng","raw_affiliation_strings":["Sun Yat-sen University,School of Data and Computer Science,Guangzhou,China","School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Data and Computer Science,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029239145","display_name":"Yifan Mao","orcid":"https://orcid.org/0009-0005-0079-8213"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Mao","raw_affiliation_strings":["Sun Yat-sen University,School of Data and Computer Science,Guangzhou,China","School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Data and Computer Science,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100707149","display_name":"Ruixuan Wang","orcid":"https://orcid.org/0000-0002-8714-0369"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruixuan Wang","raw_affiliation_strings":["Sun Yat-sen University,School of Data and Computer Science,Guangzhou,China","School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Data and Computer Science,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108050904","display_name":"Wei\u2010Shi Zheng","orcid":"https://orcid.org/0000-0001-8327-0003"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei-Shi Zheng","raw_affiliation_strings":["Sun Yat-sen University,School of Data and Computer Science,Guangzhou,China","School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Data and Computer Science,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"363","last_page":"368"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9994000196456909,"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":0.9994000196456909,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9715999960899353,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.8925255537033081},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7236589789390564},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7165915966033936},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.70096755027771},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6749867796897888},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5896538496017456},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5521921515464783},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.48404067754745483},{"id":"https://openalex.org/keywords/epilepsy","display_name":"Epilepsy","score":0.44866687059402466},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.43398451805114746},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32794320583343506},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15634649991989136},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1329733431339264},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.097421795129776}],"concepts":[{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.8925255537033081},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7236589789390564},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7165915966033936},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.70096755027771},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6749867796897888},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5896538496017456},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5521921515464783},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.48404067754745483},{"id":"https://openalex.org/C2778186239","wikidata":"https://www.wikidata.org/wiki/Q41571","display_name":"Epilepsy","level":2,"score":0.44866687059402466},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.43398451805114746},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32794320583343506},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15634649991989136},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1329733431339264},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.097421795129776},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm49941.2020.9313163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm49941.2020.9313163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1959608418","https://openalex.org/W2028034385","https://openalex.org/W2080289801","https://openalex.org/W2105497548","https://openalex.org/W2122538988","https://openalex.org/W2138160374","https://openalex.org/W2182699847","https://openalex.org/W2194775991","https://openalex.org/W2232896714","https://openalex.org/W2296289310","https://openalex.org/W2759483166","https://openalex.org/W2802766193","https://openalex.org/W2805246634","https://openalex.org/W2963773039","https://openalex.org/W2964267916","https://openalex.org/W2996179709","https://openalex.org/W3004955331"],"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/W4233722919","https://openalex.org/W2057366091","https://openalex.org/W2090763504","https://openalex.org/W4323929055"],"abstract_inverted_index":{"Epilepsy":[0],"is":[1,14,28,42,68],"one":[2],"of":[3,80,155,186],"the":[4,15,86,106,120,138,143,153,167,187],"most":[5,16],"common":[6],"neurological":[7],"diseases":[8],"in":[9,157],"humans,":[10],"and":[11,38,45,57,142,182,199],"electroencephalography":[12],"(EEG)":[13],"widely":[17],"used":[18,150],"method":[19,67,170,189],"for":[20,70],"clinicians":[21],"to":[22,30,90,100,117,151],"detect":[23,31],"epileptic":[24,32,54],"seizures.":[25],"However,":[26],"it":[27],"error-prone":[29],"seizures":[33],"by":[34,200],"manually":[35],"observing":[36],"EEG,":[37],"labeling":[39],"epilepsy":[40],"data":[41,56,89],"an":[43],"expensive":[44],"time-consuming":[46],"process.":[47],"In":[48,76],"this":[49],"study,":[50],"without":[51],"requiring":[52],"any":[53],"EEG":[55,74,88,94,109,126,160],"only":[58],"based":[59],"on":[60,73,85,123,131],"normal":[61,108,125],"EEGs,":[62],"a":[63,78,111,158],"new":[64,124,159],"selfsupervised":[65],"learning":[66],"proposed":[69,168,188],"anomaly":[71,173],"detection":[72,174],"signals.":[75],"particular,":[77],"series":[79],"scaling":[81,102,121,140,145],"transformations":[82,122,141,146],"are":[83],"performed":[84],"original":[87],"generated":[91],"self-labeled":[92,107],"scaled":[93],"data,":[95,127],"where":[96],"different":[97,101,196],"labels":[98],"correspond":[99],"transformations.":[103],"Then":[104],"using":[105],"dataset,":[110],"multi-class":[112],"classifier":[113,197],"can":[114,147],"be":[115,149],"trained":[116],"accurately":[118,130],"predict":[119],"but":[128],"not":[129],"abnormal":[132],"(epileptic)":[133],"EEGs.":[134],"The":[135,184],"inconsistency":[136],"between":[137],"predicted":[139],"groundtruth":[144],"then":[148],"measure":[152],"degree":[154],"abnormality":[156],"data.":[161],"Comprehensive":[162],"experimental":[163],"evaluations":[164],"demonstrate":[165],"that":[166],"self-supervised":[169],"outperforms":[171],"classic":[172],"methods":[175],"including":[176],"one-class":[177],"support":[178],"vector":[179],"machine":[180],"(SVM)":[181],"autoencoders.":[183],"robustness":[185],"also":[190],"has":[191],"been":[192],"empirically":[193],"proved":[194],"with":[195],"structures":[198],"varying":[201],"relevant":[202],"hyper-parameters.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}