{"id":"https://openalex.org/W3085677155","doi":"https://doi.org/10.1145/3410530.3414386","title":"Estimation of wakefulness in video-based lectures based on multimodal data fusion","display_name":"Estimation of wakefulness in video-based lectures based on multimodal data fusion","publication_year":2020,"publication_date":"2020-09-10","ids":{"openalex":"https://openalex.org/W3085677155","doi":"https://doi.org/10.1145/3410530.3414386","mag":"3085677155"},"language":"en","primary_location":{"id":"doi:10.1145/3410530.3414386","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3410530.3414386","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3410530.3414386&file=3414386-vor.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3410530.3414386&file=3414386-vor.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078145644","display_name":"Ryosuke Kawamura","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Ryosuke Kawamura","raw_affiliation_strings":["Fujitsu Laboratory Ltd., Japan"],"affiliations":[{"raw_affiliation_string":"Fujitsu Laboratory Ltd., Japan","institution_ids":["https://openalex.org/I2252096349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084776162","display_name":"Shizuka Shirai","orcid":"https://orcid.org/0000-0003-2676-3404"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"Osaka University","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shizuka Shirai","raw_affiliation_strings":["Osaka University, Japan"],"affiliations":[{"raw_affiliation_string":"Osaka University, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021744900","display_name":"Mehrasa Aizadeh","orcid":null},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"Osaka University","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Mehrasa Aizadeh","raw_affiliation_strings":["Osaka University, Japan"],"affiliations":[{"raw_affiliation_string":"Osaka University, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002778538","display_name":"Noriko Takemura","orcid":"https://orcid.org/0000-0003-1977-4690"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"Osaka University","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Noriko Takemura","raw_affiliation_strings":["Osaka University, Japan"],"affiliations":[{"raw_affiliation_string":"Osaka University, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065709581","display_name":"Hajime Nagahara","orcid":"https://orcid.org/0000-0003-1579-8767"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"Osaka University","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hajime Nagahara","raw_affiliation_strings":["Osaka University, Japan"],"affiliations":[{"raw_affiliation_string":"Osaka University, Japan","institution_ids":["https://openalex.org/I98285908"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5078145644"],"corresponding_institution_ids":["https://openalex.org/I2252096349"],"apc_list":null,"apc_paid":null,"fwci":0.537,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.70913004,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"50","last_page":"53"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9987999796867371,"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":0.9987999796867371,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/wakefulness","display_name":"Wakefulness","score":0.874210774898529},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6722152829170227},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.608088493347168},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5987077355384827},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4579026699066162},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.41483795642852783},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40180814266204834},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3748863637447357},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.23418575525283813},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.22517576813697815},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12803113460540771},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.073851078748703}],"concepts":[{"id":"https://openalex.org/C2779320081","wikidata":"https://www.wikidata.org/wiki/Q246710","display_name":"Wakefulness","level":3,"score":0.874210774898529},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6722152829170227},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.608088493347168},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5987077355384827},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4579026699066162},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.41483795642852783},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40180814266204834},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3748863637447357},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.23418575525283813},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.22517576813697815},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12803113460540771},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.073851078748703},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3410530.3414386","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3410530.3414386","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3410530.3414386&file=3414386-vor.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3410530.3414386","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3410530.3414386","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3410530.3414386&file=3414386-vor.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5899999737739563,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G7693551792","display_name":null,"funder_award_id":"(MEXT)","funder_id":"https://openalex.org/F4320320912","funder_display_name":"Ministry of Education, Culture, Sports, Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320320912","display_name":"Ministry of Education, Culture, Sports, Science and Technology","ror":"https://ror.org/048rj2z13"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3085677155.pdf","grobid_xml":"https://content.openalex.org/works/W3085677155.grobid-xml"},"referenced_works_count":10,"referenced_works":["https://openalex.org/W2033278032","https://openalex.org/W2081112272","https://openalex.org/W2148143831","https://openalex.org/W2345031027","https://openalex.org/W2594908799","https://openalex.org/W2807126412","https://openalex.org/W2949676527","https://openalex.org/W2967815566","https://openalex.org/W2972584756","https://openalex.org/W3011880926"],"related_works":["https://openalex.org/W2383588288","https://openalex.org/W2361194683","https://openalex.org/W1551231575","https://openalex.org/W4311311263","https://openalex.org/W2001567161","https://openalex.org/W2030241844","https://openalex.org/W1614439646","https://openalex.org/W2027827674","https://openalex.org/W133630538","https://openalex.org/W4240766387"],"abstract_inverted_index":{"In":[0,23,35],"distance":[1],"learning":[2,27],"contexts,":[3],"drowsiness":[4],"is":[5,14,33,163],"a":[6,40],"major":[7],"factor":[8],"which":[9,71,162],"disturbs":[10],"learning.":[11],"However,":[12],"it":[13],"not":[15],"easy":[16],"for":[17,65,91,184],"instructors":[18],"to":[19,25,55,98],"monitor":[20],"students'":[21],"wakefulness.":[22],"order":[24],"improve":[26],"efficacy,":[28],"accurate":[29],"estimation":[30,43],"of":[31,70,76,88,111,134,154,159,174],"wakefulness":[32,42,92,112,160,186],"needed.":[34],"this":[36],"study,":[37],"we":[38,94],"propose":[39],"multimodal":[41,89],"method":[44],"based":[45],"on":[46],"face":[47],"and":[48,58,62,108,125,138,144,177],"body":[49,66,78],"movement":[50],"information.":[51],"We":[52,118],"utilize":[53],"web-cameras":[54],"obtain":[56],"facial":[57,175],"head":[59],"(face-head)":[60],"movements":[61],"pressure":[63,79,130,179],"mats":[64],"movements,":[67,124],"the":[68,74,86,145,166],"latter":[69],"can":[72,181],"record":[73],"distribution":[75],"upper":[77],"while":[80],"watching":[81],"video":[82],"lectures.":[83],"To":[84],"confirm":[85],"effectiveness":[87],"data":[90,100],"estimation,":[93,161],"conducted":[95],"an":[96,150],"experiment":[97],"collect":[99],"from":[101,122,128],"students":[102],"as":[103],"they":[104],"engaged":[105],"in":[106,115,156],"e-learning":[107],"their":[109],"level":[110,140],"was":[113],"annotated":[114],"one-second":[116],"windows.":[117],"extracted":[119],"45":[120],"features":[121,127,180],"face-head":[123],"80":[126],"seat":[129,178],"data.":[131],"Two":[132],"types":[133],"fusion":[135,141,147,173],"methods,":[136],"early":[137],"decision":[139],"were":[142],"applied,":[143],"late":[146],"approach":[148],"achieved":[149],"average":[151],"F1-macro":[152],"score":[153],"0.70":[155],"three":[157],"levels":[158],"higher":[164],"than":[165],"unimodal":[167],"approach.":[168],"This":[169],"result":[170],"indicates":[171],"that":[172],"images":[176],"be":[182],"effective":[183],"learner":[185],"estimation.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}