{"id":"https://openalex.org/W7086815805","doi":"https://doi.org/10.1109/taffc.2025.3619979","title":"Automated Boredom Recognition Using Multimodal Physiological Signals","display_name":"Automated Boredom Recognition Using Multimodal Physiological Signals","publication_year":2025,"publication_date":"2025-10-09","ids":{"openalex":"https://openalex.org/W7086815805","doi":"https://doi.org/10.1109/taffc.2025.3619979"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2025.3619979","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2025.3619979","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-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":null,"display_name":"Rajamanickam Yuvaraj","orcid":"https://orcid.org/0000-0003-4526-0749"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Rajamanickam Yuvaraj","raw_affiliation_strings":["Science of Learning in Education Centre (SoLEC), Office for Research (OfR), National Institute of Education, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0003-4526-0749","affiliations":[{"raw_affiliation_string":"Science of Learning in Education Centre (SoLEC), Office for Research (OfR), National Institute of Education, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Sampathraman Samyuktha","orcid":"https://orcid.org/0009-0004-6534-5090"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Sampathraman Samyuktha","raw_affiliation_strings":["Science of Learning in Education Centre (SoLEC), Office for Research (OfR), National Institute of Education, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0009-0004-6534-5090","affiliations":[{"raw_affiliation_string":"Science of Learning in Education Centre (SoLEC), Office for Research (OfR), National Institute of Education, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jack S Fogarty","orcid":"https://orcid.org/0000-0001-6210-1067"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jack S Fogarty","raw_affiliation_strings":["Science of Learning in Education Centre (SoLEC), Office for Research (OfR), National Institute of Education, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-6210-1067","affiliations":[{"raw_affiliation_string":"Science of Learning in Education Centre (SoLEC), Office for Research (OfR), National Institute of Education, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jun Song Huang","orcid":"https://orcid.org/0000-0002-2960-7960"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jun Song Huang","raw_affiliation_strings":["Science of Learning in Education Centre (SoLEC), Office for Research (OfR), National Institute of Education, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-2960-7960","affiliations":[{"raw_affiliation_string":"Science of Learning in Education Centre (SoLEC), Office for Research (OfR), National Institute of Education, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Samuel Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I1280293394","display_name":"Ministry of Education","ror":"https://ror.org/01kcva023","country_code":"SG","type":"government","lineage":["https://openalex.org/I1280293394"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Samuel Tan","raw_affiliation_strings":["Educational Technology Division (ETD), Ministry of Education, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Educational Technology Division (ETD), Ministry of Education, Singapore","institution_ids":["https://openalex.org/I1280293394"]}]},{"author_position":"last","author":{"id":null,"display_name":"Wong Teck Kiong","orcid":null},"institutions":[{"id":"https://openalex.org/I1280293394","display_name":"Ministry of Education","ror":"https://ror.org/01kcva023","country_code":"SG","type":"government","lineage":["https://openalex.org/I1280293394"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Wong Teck Kiong","raw_affiliation_strings":["Educational Technology Division (ETD), Ministry of Education, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Educational Technology Division (ETD), Ministry of Education, Singapore","institution_ids":["https://openalex.org/I1280293394"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.576,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.74039819,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"17","issue":"1","first_page":"394","last_page":"411"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.17319999635219574,"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"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.17319999635219574,"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"}},{"id":"https://openalex.org/T10222","display_name":"Genomics and Chromatin Dynamics","score":0.12309999763965607,"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"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.0731000006198883,"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/boredom","display_name":"Boredom","score":0.8378999829292297},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5960999727249146},{"id":"https://openalex.org/keywords/gaze","display_name":"Gaze","score":0.4871000051498413},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.42649999260902405},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.399399995803833},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3993000090122223},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.3912000060081482},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.3862999975681305}],"concepts":[{"id":"https://openalex.org/C2777589236","wikidata":"https://www.wikidata.org/wiki/Q34255","display_name":"Boredom","level":2,"score":0.8378999829292297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.652400016784668},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6015999913215637},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5960999727249146},{"id":"https://openalex.org/C2779916870","wikidata":"https://www.wikidata.org/wiki/Q14467155","display_name":"Gaze","level":2,"score":0.4871000051498413},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.42649999260902405},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.399399995803833},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3993000090122223},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.3912000060081482},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.37929999828338623},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36809998750686646},{"id":"https://openalex.org/C60692881","wikidata":"https://www.wikidata.org/wiki/Q584529","display_name":"Humanoid robot","level":3,"score":0.35659998655319214},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.3239000141620636},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3142000138759613},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C6438553","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Affective computing","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C111902132","wikidata":"https://www.wikidata.org/wiki/Q1326834","display_name":"Skin conductance","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taffc.2025.3619979","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2025.3619979","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320751","display_name":"Ministry of Education - Singapore","ror":"https://ror.org/01kcva023"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Increasing":[0],"access":[1],"to":[2,21,31,96,116,171,177],"affordable":[3],"physiological":[4,61,107,158],"sensors":[5],"and":[6,71,92,98,109,137,146],"computing":[7],"devices":[8],"has":[9,24],"bolstered":[10],"the":[11,44,106,182],"development":[12],"of":[13,47,188],"emotionaware":[14],"systems":[15,149],"that":[16],"recognize":[17],"human":[18],"emotions.":[19],"However,":[20],"date,":[22],"there":[23],"been":[25],"little":[26],"research":[27],"testing":[28],"machine-driven":[29],"approaches":[30],"recognizing":[32],"boredom,":[33],"particularly":[34],"in":[35,162],"learning":[36],"contexts.":[37],"To":[38],"address":[39],"that,":[40],"this":[41],"study":[42],"tests":[43,114],"automatic":[45],"recognition":[46,57,122,148,168,186],"boredom":[48,121,185],"induced":[49],"during":[50],"a":[51,55],"video":[52],"lecture":[53],"using":[54,111,156],"multimodal":[56,147],"system":[58],"relying":[59],"on":[60],"signals.":[62],"Electroencephalogram":[63],"(EEG),":[64],"electrocardiogram":[65],"(ECG),":[66],"galvanic":[67],"skin":[68],"response":[69],"(GSR),":[70],"eye":[72,196],"gaze":[73,197],"data":[74,108],"were":[75,103,150],"recorded":[76,192],"from":[77,105],"84":[78],"healthy":[79],"adults":[80],"(mean":[81],"age":[82],"=":[83],"26.90":[84],"\u00b1":[85,190],"5.29)":[86],"as":[87],"they":[88],"watched":[89],"both":[90],"non-boring":[91],"boring":[93],"educational":[94],"videos":[95],"control":[97],"induce":[99],"boredom.":[100],"Signal":[101],"features":[102],"extracted":[104],"validated":[110],"Wilcoxon":[112],"signed-rank":[113],"prior":[115],"evaluating":[117,153],"their":[118],"utility":[119],"for":[120,193],"with":[123,141,181,200],"three":[124],"separate":[125],"machine-learning":[126],"classification":[127],"techniques,":[128],"namely":[129],"Extreme":[130],"Gradient":[131,138],"Boosting":[132,139],"(XGB),":[133],"Random":[134],"Forest":[135],"(RF),":[136],"(GB),":[140],"leave-one-out":[142],"cross-validation.":[143],"Both":[144],"unimodal":[145],"assessed":[151],"by":[152],"model":[154,173],"performance":[155,174],"each":[157],"signal":[159],"separately":[160],"or":[161],"combination":[163],"(using":[164],"decision":[165],"fusion).":[166],"Multimodal":[167],"was":[169],"found":[170],"enhance":[172],"when":[175],"compared":[176],"any":[178],"single":[179],"modality,":[180],"highest":[183],"average":[184],"accuracy":[187],"88.56%":[189],"0.82%":[191],"EEG":[194],"+":[195],"modal":[198],"fusion":[199],"RF.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}