{"id":"https://openalex.org/W7224625653","doi":"https://doi.org/10.3390/brainsci16111183","title":"Participant-Specific Adaptive Label Smoothing Using Subjective Workload Responses for Cognitive Workload Classification from EEG","display_name":"Participant-Specific Adaptive Label Smoothing Using Subjective Workload Responses for Cognitive Workload Classification from EEG","publication_year":2026,"publication_date":"2026-10-29","ids":{"openalex":"https://openalex.org/W7224625653","doi":"https://doi.org/10.3390/brainsci16111183"},"language":"en","primary_location":{"id":"doi:10.3390/brainsci16111183","doi":"https://doi.org/10.3390/brainsci16111183","is_oa":true,"landing_page_url":"https://doi.org/10.3390/brainsci16111183","pdf_url":null,"source":{"id":"https://openalex.org/S122317144","display_name":"Brain Sciences","issn_l":"2076-3425","issn":["2076-3425"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","norway-1","poland-100","russia-white-list-3","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Brain Sciences","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/brainsci16111183","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057494227","display_name":"Agnieszka Wosiak","orcid":"https://orcid.org/0000-0001-6124-1236","observed_orcids":["https://orcid.org/0000-0001-6124-1236","https://orcid.org/0009-0009-2861-3486"]},"institutions":[{"id":"https://openalex.org/I188884621","display_name":"Lodz University of Technology","ror":"https://ror.org/00s8fpf52","country_code":"PL","type":"education","lineage":["https://openalex.org/I188884621"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Agnieszka Wosiak","raw_affiliation_strings":["Institute of Information Technology, Lodz University of Technology, al. Politechniki 8, 93-590 \u0141\u00f3d\u017a, Poland"],"raw_orcid":"https://orcid.org/0000-0001-6124-1236","affiliations":[{"raw_affiliation_string":"Institute of Information Technology, Lodz University of Technology, al. Politechniki 8, 93-590 \u0141\u00f3d\u017a, Poland","institution_ids":["https://openalex.org/I188884621"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120207201","display_name":"Emilia Stodulska","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I188884621","display_name":"Lodz University of Technology","ror":"https://ror.org/00s8fpf52","country_code":"PL","type":"education","lineage":["https://openalex.org/I188884621"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Emilia Stodulska","raw_affiliation_strings":["Institute of Information Technology, Lodz University of Technology, al. Politechniki 8, 93-590 \u0141\u00f3d\u017a, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Technology, Lodz University of Technology, al. Politechniki 8, 93-590 \u0141\u00f3d\u017a, Poland","institution_ids":["https://openalex.org/I188884621"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5093448589","display_name":"Katarzyna \u017bykwi\u0144ska","orcid":"https://orcid.org/0009-0004-8364-2777","observed_orcids":["https://orcid.org/0009-0004-8364-2777"]},"institutions":[{"id":"https://openalex.org/I188884621","display_name":"Lodz University of Technology","ror":"https://ror.org/00s8fpf52","country_code":"PL","type":"education","lineage":["https://openalex.org/I188884621"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Katarzyna \u017bykwi\u0144ska","raw_affiliation_strings":["Institute of Information Technology, Lodz University of Technology, al. Politechniki 8, 93-590 \u0141\u00f3d\u017a, Poland"],"raw_orcid":"https://orcid.org/0009-0004-8364-2777","affiliations":[{"raw_affiliation_string":"Institute of Information Technology, Lodz University of Technology, al. Politechniki 8, 93-590 \u0141\u00f3d\u017a, Poland","institution_ids":["https://openalex.org/I188884621"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5057494227"],"corresponding_institution_ids":["https://openalex.org/I188884621"],"apc_list":{"value":2200,"currency":"CHF","value_usd":2654},"apc_paid":{"value":2200,"currency":"CHF","value_usd":2654},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.85656747,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"11","first_page":"1183","last_page":"1183"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9794999957084656,"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":0.9794999957084656,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.01269999984651804,"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/T10525","display_name":"Human-Automation Interaction and Safety","score":0.005400000140070915,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/electroencephalography","display_name":"EEG","score":0.7940000295639038},{"id":"https://openalex.org/keywords/perceived-workload","display_name":"perceived workload","score":0.7549999952316284},{"id":"https://openalex.org/keywords/inter-individual-variability","display_name":"interindividual variability","score":0.8519999980926514},{"id":"https://openalex.org/keywords/swin-transformer","display_name":"Swin Transformer","score":0.6869999766349792},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8769999742507935},{"id":"https://openalex.org/keywords/time-frequency-representation","display_name":"time-frequency representation","score":0.7429999709129333}],"concepts":[{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.8424999713897705},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.715399980545044},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6488000154495239},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6412000060081482},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5845999717712402},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5738999843597412},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4625000059604645},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.4537999927997589},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.4099999964237213},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3944999873638153},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36890000104904175},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3569999933242798},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3425999879837036},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.32330000400543213},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.30730000138282776},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2888000011444092},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C119653847","wikidata":"https://www.wikidata.org/wiki/Q1327780","display_name":"Elementary cognitive task","level":3,"score":0.27059999108314514},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.2619999945163727},{"id":"https://openalex.org/C52970973","wikidata":"https://www.wikidata.org/wiki/Q2497134","display_name":"Adaptive system","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/brainsci16111183","doi":"https://doi.org/10.3390/brainsci16111183","is_oa":true,"landing_page_url":"https://doi.org/10.3390/brainsci16111183","pdf_url":null,"source":{"id":"https://openalex.org/S122317144","display_name":"Brain Sciences","issn_l":"2076-3425","issn":["2076-3425"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","norway-1","poland-100","russia-white-list-3","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Brain Sciences","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/brainsci16111183","doi":"https://doi.org/10.3390/brainsci16111183","is_oa":true,"landing_page_url":"https://doi.org/10.3390/brainsci16111183","pdf_url":null,"source":{"id":"https://openalex.org/S122317144","display_name":"Brain Sciences","issn_l":"2076-3425","issn":["2076-3425"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","norway-1","poland-100","russia-white-list-3","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Brain Sciences","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4000000059604645,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2106822551","https://openalex.org/W2146182319","https://openalex.org/W2183341477","https://openalex.org/W2894692871","https://openalex.org/W3127641795","https://openalex.org/W3128254639","https://openalex.org/W3138516171","https://openalex.org/W4220781804","https://openalex.org/W4280622938","https://openalex.org/W4300819149","https://openalex.org/W4319970836","https://openalex.org/W4382119270","https://openalex.org/W4382237530","https://openalex.org/W4386071461","https://openalex.org/W4386075939","https://openalex.org/W4389274747","https://openalex.org/W4390873670","https://openalex.org/W4391403644","https://openalex.org/W4394684824","https://openalex.org/W4394984563","https://openalex.org/W4395704164","https://openalex.org/W4399727977","https://openalex.org/W4401630302","https://openalex.org/W4401976276","https://openalex.org/W4402773018","https://openalex.org/W4403259613","https://openalex.org/W4404313184","https://openalex.org/W4406064869","https://openalex.org/W4408868020","https://openalex.org/W4408917650","https://openalex.org/W4409290412","https://openalex.org/W4413905162","https://openalex.org/W4414189152","https://openalex.org/W7165678874","https://openalex.org/W7197052440","https://openalex.org/W7203820170"],"related_works":["https://openalex.org/W7168130022","https://openalex.org/W7152603110","https://openalex.org/W7161725457","https://openalex.org/W7161759045","https://openalex.org/W4385763691","https://openalex.org/W3163690385","https://openalex.org/W7138955123","https://openalex.org/W3207383179","https://openalex.org/W2735390493","https://openalex.org/W7117971141"],"abstract_inverted_index":{"Background:":[0],"Cognitive":[1],"workload":[2,16,30,153],"classification":[3,63],"from":[4,100],"electroencephalography":[5],"is":[6],"affected":[7],"by":[8],"interindividual":[9],"variability":[10],"in":[11,24,28,175],"EEG":[12,106],"signals":[13],"and":[14,33,55,72,84,127,129,135,178],"subjective":[15,152],"responses.":[17],"We":[18],"propose":[19],"participant-specific":[20,85,94,151,169],"adaptive":[21,112],"label":[22,113],"smoothing,":[23],"which":[25],"the":[26,37,41,52,116,163,172,188],"change":[27],"perceived":[29],"between":[31],"resting":[32],"task":[34],"conditions":[35],"controls":[36],"target":[38,160,176],"confidence,":[39,161],"while":[40],"experimental":[42],"class":[43],"remains":[44],"unchanged.":[45],"Methods:":[46],"The":[47,93,147],"method":[48],"was":[49,186],"evaluated":[50,89],"on":[51,80],"STEW":[53],"dataset":[54],"compared":[56],"with":[57,123,162],"five":[58],"alternative":[59],"supervision":[60],"strategies.":[61],"Two":[62],"models":[64],"were":[65,88],"used:":[66],"a":[67,73],"feature-based":[68],"convolutional":[69],"neural":[70],"network":[71,77],"multi-scale":[74],"Swin":[75],"Transformer":[76],"(MST-Net)":[78],"operating":[79],"time-frequency":[81],"representations.":[82],"Global":[83],"stratified":[86,110],"normalization":[87,97],"using":[90],"participant-disjoint":[91],"cross-validation.":[92],"approach":[95],"used":[96,157],"statistics":[98],"estimated":[99],"each":[101],"unseen":[102],"participant\u2019s":[103],"own":[104],"unlabeled":[105],"data.":[107],"Results:":[108],"Under":[109],"normalization,":[111],"smoothing":[114],"produced":[115],"highest":[117],"macro":[118],"F1":[119],"for":[120,143],"both":[121,144],"models,":[122],"values":[124,132],"of":[125,133],"0.768":[126],"0.796,":[128],"ROC":[130],"AUC":[131],"0.844":[134],"0.878,":[136],"respectively.":[137],"It":[138],"also":[139],"maintained":[140],"high":[141],"recall":[142],"classes.":[145],"Conclusions:":[146],"findings":[148],"suggest":[149],"that":[150],"responses":[154],"can":[155],"be":[156],"to":[158],"modulate":[159],"most":[164],"consistent":[165],"benefit":[166],"observed":[167],"under":[168],"normalization.":[170],"As":[171],"strategies":[173],"differ":[174],"definitions":[177],"no":[179],"hard":[180],"rest/task":[181],"or":[182],"fixed":[183],"label-smoothing":[184],"control":[185],"evaluated,":[187],"differences":[189],"are":[190],"descriptive.":[191]},"counts_by_year":[],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2026-10-30T00:00:00"}