{"id":"https://openalex.org/W7167612896","doi":"https://doi.org/10.1109/access.2026.3710652","title":"Bidirectional LSTM-Based Temporal Estimation of Cognitive Fatigue in Human\u2013Robot Interaction From Physiological Signals: A Deployment-Oriented Pilot Study","display_name":"Bidirectional LSTM-Based Temporal Estimation of Cognitive Fatigue in Human\u2013Robot Interaction From Physiological Signals: A Deployment-Oriented Pilot Study","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7167612896","doi":"https://doi.org/10.1109/access.2026.3710652"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3710652","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3710652","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3710652","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065609205","display_name":"Manizheh Zand","orcid":"https://orcid.org/0000-0002-1745-8523"},"institutions":[{"id":"https://openalex.org/I16269868","display_name":"Santa Clara University","ror":"https://ror.org/03ypqe447","country_code":"US","type":"education","lineage":["https://openalex.org/I16269868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manizheh Zand","raw_affiliation_strings":["Santa Clara University"],"raw_orcid":"https://orcid.org/0000-0002-1745-8523","affiliations":[{"raw_affiliation_string":"Santa Clara University","institution_ids":["https://openalex.org/I16269868"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140174493","display_name":"Glenn R. Wylie","orcid":null},"institutions":[{"id":"https://openalex.org/I250153783","display_name":"Kessler Foundation","ror":"https://ror.org/05hacyq28","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I250153783"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Glenn R. Wylie","raw_affiliation_strings":["Kessler Foundation"],"raw_orcid":"https://orcid.org/0000-0002-7061-6658","affiliations":[{"raw_affiliation_string":"Kessler Foundation","institution_ids":["https://openalex.org/I250153783"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140222159","display_name":"Andrew Wolfe","orcid":"https://orcid.org/0000-0002-0788-1432"},"institutions":[{"id":"https://openalex.org/I16269868","display_name":"Santa Clara University","ror":"https://ror.org/03ypqe447","country_code":"US","type":"education","lineage":["https://openalex.org/I16269868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Wolfe","raw_affiliation_strings":["Santa Clara University"],"raw_orcid":"https://orcid.org/0000-0002-0788-1432","affiliations":[{"raw_affiliation_string":"Santa Clara University","institution_ids":["https://openalex.org/I16269868"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059487972","display_name":"Maria Kyrarini","orcid":"https://orcid.org/0000-0003-0968-2477"},"institutions":[{"id":"https://openalex.org/I16269868","display_name":"Santa Clara University","ror":"https://ror.org/03ypqe447","country_code":"US","type":"education","lineage":["https://openalex.org/I16269868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maria Kyrarini","raw_affiliation_strings":["Santa Clara University"],"raw_orcid":"https://orcid.org/0000-0003-0968-2477","affiliations":[{"raw_affiliation_string":"Santa Clara University","institution_ids":["https://openalex.org/I16269868"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.85983477,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"105352","last_page":"105374"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.5042999982833862,"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"}},"topics":[{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.5042999982833862,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.22290000319480896,"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":0.02630000002682209,"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/cognition","display_name":"Cognition","score":0.47609999775886536},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4108999967575073},{"id":"https://openalex.org/keywords/neurophysiology","display_name":"Neurophysiology","score":0.34279999136924744},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.2971000075340271},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.2854999899864197},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.2653999924659729}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6158000230789185},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.47609999775886536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41290000081062317},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4108999967575073},{"id":"https://openalex.org/C152478114","wikidata":"https://www.wikidata.org/wiki/Q660910","display_name":"Neurophysiology","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.2854999899864197},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.28369998931884766},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2653999924659729},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C2776874296","wikidata":"https://www.wikidata.org/wiki/Q6940317","display_name":"Muscle fatigue","level":3,"score":0.25220000743865967},{"id":"https://openalex.org/C2982735371","wikidata":"https://www.wikidata.org/wiki/Q9690","display_name":"Mental fatigue","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3710652","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3710652","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b7568c616f59484d9124ce5d2aa4e0d6","is_oa":false,"landing_page_url":"https://doaj.org/article/b7568c616f59484d9124ce5d2aa4e0d6","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 105352-105374 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3710652","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3710652","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Continuous":[0],"awareness":[1],"of":[2,98,190,237],"Cognitive":[3],"Fatigue":[4,65],"(CF)":[5],"is":[6,79,107,138,154],"important":[7],"for":[8,44,64,109],"safe":[9],"and":[10,20,54,81,91,117,184,208,216],"effective":[11],"Human-Robot":[12],"Interaction":[13],"(HRI),":[14],"yet":[15],"physiological":[16,145,173],"responses":[17],"are":[18],"non-stationary":[19],"vary":[21],"substantially":[22],"across":[23,125],"individuals,":[24],"making":[25],"deployment":[26],"on":[27,86,94,227],"previously":[28,115,228],"unseen":[29,116,229],"users":[30],"challenging.":[31],"This":[32],"paper":[33],"presents":[34],"a":[35,68],"Bidirectional":[36],"Long":[37],"Short":[38],"Term":[39],"Memory":[40],"(Bi-LSTM)-based":[41],"temporal":[42,235],"framework":[43],"post-scenario":[45,168,243],"CF":[46,244],"estimation":[47,245],"in":[48],"HRI":[49,159],"from":[50,88],"multimodal":[51,238],"Electrocardiography":[52],"(ECG)":[53],"Electrodermal":[55],"Activity":[56],"(EDA)":[57],"time":[58],"series,":[59],"using":[60,83],"Visual":[61],"Analogue":[62],"Scale":[63],"(VAS-F)":[66],"as":[67,112,114,162],"continuous-valued":[69],"regression":[70,130],"target.":[71],"To":[72,120],"better":[73],"reflect":[74],"real-world":[75],"operation,":[76],"the":[77,199,202],"model":[78,204],"trained":[80],"validated":[82],"participant-level":[84],"cross-validation":[85],"data":[87],"16":[89],"individuals":[90],"subsequently":[92],"evaluated":[93],"an":[95,128],"independent":[96,200],"cohort":[97],"23":[99],"participants":[100,111],"without":[101],"subject-specific":[102],"calibration":[103],"or":[104],"fine-tuning.":[105],"Performance":[106],"reported":[108],"all":[110],"well":[113],"overlapping":[118],"subsets.":[119],"address":[121],"unequal":[122],"prediction":[123],"difficulty":[124],"fatigue":[126,169],"transitions,":[127],"error-aware":[129],"objective":[131],"Focal":[132],"Root":[133,177],"Mean":[134,178],"Squared":[135,179],"Error":[136,180],"(FocalRMSE)":[137],"introduced":[139],"to":[140,143],"increase":[141],"sensitivity":[142],"high-uncertainty":[144],"states":[146],"during":[147],"training.":[148],"A":[149],"baseline":[150],"(pre-scenario)":[151],"VAS-F":[152],"score":[153],"provided":[155],"once":[156],"per":[157],"structured":[158],"task":[160],"episode":[161],"contextual":[163],"input,":[164],"while":[165],"predictions":[166],"target":[167],"driven":[170],"by":[171],"within-episode":[172],"dynamics.":[174],"Cross-validation":[175],"achieves":[176,205],"(RMSE)":[181],"=":[182,196,212,218,224],"6.53":[183],"<inline-formula>":[185,209,221],"<tex-math":[186,193,210,222],"notation=\"LaTeX\">$R^{2}$":[187,194],"</tex-math></inline-formula>":[188,214,226],"(coefficient":[189],"determination)":[191],"(<inline-formula>":[192],"</tex-math></inline-formula>)":[195],"0.90.":[197],"On":[198],"cohort,":[201],"frozen":[203],"RMSE=":[206],"7.06":[207],"notation=\"LaTeX\">$R^{2}":[211,223],"0.90$":[213],"overall,":[215],"RMSE":[217],"7.62":[219],"with":[220],"0.76$":[225],"participants.":[230],"These":[231],"results":[232],"indicate":[233],"that":[234],"modeling":[236],"physiology":[239],"can":[240],"support":[241],"calibration-free":[242],"under":[246],"cross-participant":[247],"evaluation.":[248]},"counts_by_year":[],"updated_date":"2026-07-25T15:57:00.446498","created_date":"2026-07-08T00:00:00"}