{"id":"https://openalex.org/W4205155768","doi":"https://doi.org/10.1109/smc52423.2021.9658662","title":"Exploring Conventional, Automated and Deep Machine Learning for Electrodermal Activity-Based Drivers\u2019 Stress Recognition","display_name":"Exploring Conventional, Automated and Deep Machine Learning for Electrodermal Activity-Based Drivers\u2019 Stress Recognition","publication_year":2021,"publication_date":"2021-10-17","ids":{"openalex":"https://openalex.org/W4205155768","doi":"https://doi.org/10.1109/smc52423.2021.9658662"},"language":"en","primary_location":{"id":"doi:10.1109/smc52423.2021.9658662","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc52423.2021.9658662","pdf_url":null,"source":{"id":"https://openalex.org/S4363607761","display_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5074803723","display_name":"Katharina Lingelbach","orcid":"https://orcid.org/0000-0003-1895-1667"},"institutions":[{"id":"https://openalex.org/I129877168","display_name":"Carl von Ossietzky Universit\u00e4t Oldenburg","ror":"https://ror.org/033n9gh91","country_code":"DE","type":"education","lineage":["https://openalex.org/I129877168"]},{"id":"https://openalex.org/I3020504353","display_name":"Fraunhofer Institute for Industrial Engineering","ror":"https://ror.org/01nh64743","country_code":"DE","type":"facility","lineage":["https://openalex.org/I3020504353","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Katharina Lingelbach","raw_affiliation_strings":["Applied Neurocognitive Psychology Lab, University of Oldenburg, Oldenburg, Germany","Fraunhofer Institute for Industrial Engineering IAO, Stuttgart, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Applied Neurocognitive Psychology Lab, University of Oldenburg, Oldenburg, Germany","institution_ids":["https://openalex.org/I129877168"]},{"raw_affiliation_string":"Fraunhofer Institute for Industrial Engineering IAO, Stuttgart, Germany","institution_ids":["https://openalex.org/I3020504353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110831742","display_name":"Michael Bui","orcid":"https://orcid.org/0009-0006-5953-6266"},"institutions":[{"id":"https://openalex.org/I3020504353","display_name":"Fraunhofer Institute for Industrial Engineering","ror":"https://ror.org/01nh64743","country_code":"DE","type":"facility","lineage":["https://openalex.org/I3020504353","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Bui","raw_affiliation_strings":["Fraunhofer Institute for Industrial Engineering IAO, Stuttgart, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Industrial Engineering IAO, Stuttgart, Germany","institution_ids":["https://openalex.org/I3020504353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065967898","display_name":"Frederik Diederichs","orcid":"https://orcid.org/0000-0002-8600-6176"},"institutions":[{"id":"https://openalex.org/I3020504353","display_name":"Fraunhofer Institute for Industrial Engineering","ror":"https://ror.org/01nh64743","country_code":"DE","type":"facility","lineage":["https://openalex.org/I3020504353","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Frederik Diederichs","raw_affiliation_strings":["Fraunhofer Institute for Industrial Engineering IAO, Stuttgart, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Industrial Engineering IAO, Stuttgart, Germany","institution_ids":["https://openalex.org/I3020504353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033952470","display_name":"Mathias Vukeli\u0107","orcid":"https://orcid.org/0000-0003-1593-6963"},"institutions":[{"id":"https://openalex.org/I3020504353","display_name":"Fraunhofer Institute for Industrial Engineering","ror":"https://ror.org/01nh64743","country_code":"DE","type":"facility","lineage":["https://openalex.org/I3020504353","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mathias Vukelic","raw_affiliation_strings":["Fraunhofer Institute for Industrial Engineering IAO, Stuttgart, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Industrial Engineering IAO, Stuttgart, Germany","institution_ids":["https://openalex.org/I3020504353"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1339","last_page":"1344"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9948999881744385,"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":0.9948999881744385,"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":0.9933000206947327,"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":0.9793999791145325,"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/stress","display_name":"Stress (linguistics)","score":0.5951825976371765},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5863761901855469},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4674787223339081},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4109058678150177},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3949466049671173},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3718910813331604}],"concepts":[{"id":"https://openalex.org/C21036866","wikidata":"https://www.wikidata.org/wiki/Q181767","display_name":"Stress (linguistics)","level":2,"score":0.5951825976371765},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5863761901855469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4674787223339081},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4109058678150177},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3949466049671173},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3718910813331604},{"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":2,"locations":[{"id":"doi:10.1109/smc52423.2021.9658662","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc52423.2021.9658662","pdf_url":null,"source":{"id":"https://openalex.org/S4363607761","display_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},{"id":"pmh:oai:publica.fraunhofer.de:publica/504702","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/504702","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1239497932","https://openalex.org/W1515135833","https://openalex.org/W1677182931","https://openalex.org/W1980832965","https://openalex.org/W2005534705","https://openalex.org/W2043756605","https://openalex.org/W2051640322","https://openalex.org/W2066460280","https://openalex.org/W2076807218","https://openalex.org/W2095898844","https://openalex.org/W2101234009","https://openalex.org/W2131274108","https://openalex.org/W2134853975","https://openalex.org/W2157289187","https://openalex.org/W2171801645","https://openalex.org/W2338065342","https://openalex.org/W2370305143","https://openalex.org/W2593144425","https://openalex.org/W2622397598","https://openalex.org/W2751088292","https://openalex.org/W2808698744","https://openalex.org/W2910424258","https://openalex.org/W2932628637","https://openalex.org/W2937732310","https://openalex.org/W2955219525","https://openalex.org/W2965898164","https://openalex.org/W2966284335","https://openalex.org/W2968963421","https://openalex.org/W2972883610","https://openalex.org/W2984913259","https://openalex.org/W3006499155","https://openalex.org/W3015226328","https://openalex.org/W3016531141","https://openalex.org/W3094893237","https://openalex.org/W3099085560","https://openalex.org/W3127637041","https://openalex.org/W3128284736","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W4321369474","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3046775127","https://openalex.org/W3082895349"],"abstract_inverted_index":{"Stress":[0],"and":[1,16,45,90,112,127,130,151,208,236,286],"cognitive":[2,134],"overload":[3],"during":[4,282],"driving":[5,47,104,124,284],"are":[6,168],"associated":[7],"with":[8,41,83,145,171,239],"decreased":[9],"performance":[10,175,231],"potentially":[11],"leading":[12],"to":[13,29,94,233,250,264],"serious":[14],"mistakes":[15],"even":[17],"fatal":[18],"incidents.":[19],"Therefore,":[20],"research":[21],"on":[22,278],"drivers’":[23,96],"mental":[24],"states":[25,98,109],"recognition":[26],"is":[27,60],"promising":[28],"reduce":[30],"these":[31],"traffic":[32],"accidents":[33],"caused":[34],"by":[35,161,274],"human":[36],"error":[37],"(e.g.,":[38],"in":[39,102,230],"combination":[40],"driver":[42],"assistance":[43],"systems":[44],"automated":[46,86,128],"functions).":[48],"Easy-to-use,":[49],"unobtrusive":[50],"wearables":[51],"allow":[52],"convenient":[53],"measurement":[54],"of":[55,76,122,148,197,213],"electrodermal":[56],"activity":[57],"(EDA)":[58],"which":[59],"an":[61,177],"informative":[62],"measure":[63],"for":[64,255,296],"the":[65,74,119,123,149,187,214,223,234,260,266],"experienced":[66],"stress":[67,97,108,189],"level.":[68],"In":[69,259],"this":[70],"article,":[71],"we":[72,262],"explore":[73],"potential":[75],"various":[77],"conventional":[78,235],"machine":[79],"learning":[80,92],"(ML)":[81],"models":[82,238,269],"hand-crafted":[84],"features,":[85],"pipeline":[87,159],"optimization":[88],"(AutoML),":[89],"deep":[91],"(DL)":[93],"recognize":[95],"from":[99],"EDA":[100,153],"recordings":[101],"a":[103,140,158,172,183,193,289],"simulator.":[105],"Three":[106],"different":[107],"(low,":[110],"mid,":[111],"high":[113,173],"stress)":[114],"were":[115],"induced":[116],"via":[117,163,182],"(a)":[118,277],"complexity":[120],"level":[121,180],"task":[125],"(manual":[126],"driving)":[129],"(b)":[131,287],"simultaneous":[132],"secondary":[133],"tasks.":[135],"Our":[136,242],"results":[137,243],"reveal":[138],"that":[139,245],"k-nearest":[141],"neighbors":[142],"(KNN)":[143],"classifier":[144,212],"handcrafted":[146,240],"features":[147],"phasic":[150],"tonic":[152],"response":[154],"as":[155,157],"well":[156],"suggested":[160],"AutoML":[162,237,246],"Tree-Based":[164],"Pipeline":[165],"Optimization":[166],"(TPOT)":[167],"particularly":[169],"suited":[170],"classification":[174],"above":[176],"empirical":[178],"chance":[179],"estimated":[181],"dummy":[184],"classifier.":[185],"Predicting":[186],"three":[188],"levels,":[190],"they":[191],"achieved":[192],"bootstrapped":[194],"balanced":[195],"accuracy":[196],"63.7":[198],"%":[199,202,210,217],"(KNN;":[200],"95":[201,216],"confidence":[203],"interval":[204],"(CI):":[205],"[36.7,":[206],"86.7])":[207],"71.6":[209],"(stacking":[211],"AutoML;":[215],"CI:":[218],"[50.0,":[219],"90.0]),":[220],"respectively.":[221],"Interestingly,":[222],"DL":[224],"model":[225,295],"architecture":[226],"was":[227],"not":[228],"superior":[229],"compared":[232],"features.":[241],"propose":[244],"might":[247],"be":[248],"beneficial":[249],"find":[251],"optimal":[252],"ML":[253],"pipelines":[254],"EDA-based":[256],"state":[257],"recognition.":[258],"future,":[261],"aim":[263],"evaluate":[265],"here":[267],"proposed":[268],"regarding":[270],"their":[271],"generalization":[272],"ability":[273],"applying":[275],"them":[276],"new":[279],"datasets":[280],"collected":[281],"realistic":[283],"scenarios":[285],"within":[288],"subject-independent":[290],"approach":[291],"(i.e.,":[292],"training":[293],"one":[294],"all":[297],"subjects).":[298]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}