{"id":"https://openalex.org/W3210354869","doi":"https://doi.org/10.32604/cmc.2022.022553","title":"Hypo-Driver: A Multiview Driver Fatigue and Distraction Level Detection System","display_name":"Hypo-Driver: A Multiview Driver Fatigue and Distraction Level Detection System","publication_year":2021,"publication_date":"2021-11-02","ids":{"openalex":"https://openalex.org/W3210354869","doi":"https://doi.org/10.32604/cmc.2022.022553","mag":"3210354869"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2022.022553","doi":"https://doi.org/10.32604/cmc.2022.022553","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2022.022553","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","ki-jl-1","norway-1","poland-20","russia-white-list-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2022.022553","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001503415","display_name":"Fabi\u00e1n Riquelme","orcid":"https://orcid.org/0000-0003-4491-0148","observed_orcids":["https://orcid.org/0000-0003-4491-0148"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fabi\u91a4 Riquelme","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112700974","display_name":"Rodrigo Olivares","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rodrigo Olivares","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083262833","display_name":"Francisco Mu\u00f1oz","orcid":"https://orcid.org/0000-0002-3853-6156","observed_orcids":["https://orcid.org/0000-0002-3853-6156"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Francisco Mu\u99c9z","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013368755","display_name":"Xavier Molinero","orcid":"https://orcid.org/0000-0002-5203-4347","observed_orcids":["https://orcid.org/0000-0002-5203-4347"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xavier Molinero","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5033912650","display_name":"Mar\u0131\u0301a Serna","orcid":"https://orcid.org/0000-0001-9729-8648","observed_orcids":["https://orcid.org/0000-0001-9729-8648"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maria Serna","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.2215,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.94605972,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"71","issue":"1","first_page":"1999","last_page":"2007"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9243000149726868,"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":0.9243000149726868,"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":0.04769999906420708,"subfield":{"id":"https://openalex.org/subfields/3307","display_name":"Human Factors and Ergonomics"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.004800000227987766,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/driver-fatigue-detection","display_name":"driver fatigue detection","score":0.9879999756813049},{"id":"https://openalex.org/keywords/driver-distraction-detection","display_name":"driver distraction detection","score":0.9309999942779541},{"id":"https://openalex.org/keywords/hypovigilance","display_name":"hypovigilance","score":0.8460000157356262},{"id":"https://openalex.org/keywords/driver-inattention","display_name":"driver inattention","score":0.6679999828338623},{"id":"https://openalex.org/keywords/facial-expression-analysis","display_name":"facial expression analysis","score":0.7879999876022339},{"id":"https://openalex.org/keywords/physiological-signals","display_name":"physiological signals","score":0.640999972820282},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"EEG","score":0.7900000214576721},{"id":"https://openalex.org/keywords/ecg","display_name":"ECG","score":0.9480000138282776},{"id":"https://openalex.org/keywords/surface-electromyography","display_name":"surface electromyography","score":0.9020000100135803},{"id":"https://openalex.org/keywords/electrooculography","display_name":"electrooculography","score":0.9200000166893005},{"id":"https://openalex.org/keywords/perclos","display_name":"PERCLOS","score":0.8460000157356262},{"id":"https://openalex.org/keywords/eye-aspect-ratio","display_name":"eye aspect ratio","score":0.8569999933242798},{"id":"https://openalex.org/keywords/mouth-aspect-ratio","display_name":"mouth aspect ratio","score":0.9589999914169312},{"id":"https://openalex.org/keywords/blink-rate","display_name":"blink rate","score":0.796999990940094},{"id":"https://openalex.org/keywords/multimodal-fusion","display_name":"multimodal fusion","score":0.8709999918937683},{"id":"https://openalex.org/keywords/deep-residual-neural-network","display_name":"deep residual neural network","score":0.8230000138282776},{"id":"https://openalex.org/keywords/lstm-rnn","display_name":"LSTM-RNN","score":0.7310000061988831},{"id":"https://openalex.org/keywords/drowsiness-detection","display_name":"drowsiness detection","score":0.6639999747276306}],"concepts":[{"id":"https://openalex.org/C2776378700","wikidata":"https://www.wikidata.org/wiki/Q3030775","display_name":"Distraction","level":2,"score":0.7154317498207092},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.658496618270874},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5872687697410583},{"id":"https://openalex.org/C2776465824","wikidata":"https://www.wikidata.org/wiki/Q5283083","display_name":"Distracted driving","level":3,"score":0.5711374282836914},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5537875890731812},{"id":"https://openalex.org/C2778681526","wikidata":"https://www.wikidata.org/wiki/Q420647","display_name":"Electrooculography","level":3,"score":0.5165082812309265},{"id":"https://openalex.org/C2779055241","wikidata":"https://www.wikidata.org/wiki/Q644240","display_name":"Biosignal","level":3,"score":0.4965839982032776},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.485128253698349},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.4492619037628174},{"id":"https://openalex.org/C200678441","wikidata":"https://www.wikidata.org/wiki/Q1423044","display_name":"Alertness","level":2,"score":0.42695334553718567},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.414528489112854},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39254626631736755},{"id":"https://openalex.org/C153050134","wikidata":"https://www.wikidata.org/wiki/Q760256","display_name":"Eye movement","level":2,"score":0.31224673986434937},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10592705011367798},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2022.022553","doi":"https://doi.org/10.32604/cmc.2022.022553","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2022.022553","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","ki-jl-1","norway-1","poland-20","russia-white-list-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2022.022553","doi":"https://doi.org/10.32604/cmc.2022.022553","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2022.022553","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","ki-jl-1","norway-1","poland-20","russia-white-list-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1973996240","https://openalex.org/W2001726698","https://openalex.org/W2067964981","https://openalex.org/W2076587863","https://openalex.org/W2105334447","https://openalex.org/W2172717914","https://openalex.org/W2371731424","https://openalex.org/W2556398113","https://openalex.org/W2558193840","https://openalex.org/W2591379487","https://openalex.org/W2593216954","https://openalex.org/W2600728771","https://openalex.org/W2606557993","https://openalex.org/W2743916180","https://openalex.org/W2765992395","https://openalex.org/W2773325192","https://openalex.org/W2882972003","https://openalex.org/W2883597459","https://openalex.org/W2897051344","https://openalex.org/W2901607170","https://openalex.org/W2904249184","https://openalex.org/W2942685890","https://openalex.org/W2943512776","https://openalex.org/W2947667983","https://openalex.org/W2948914987","https://openalex.org/W2965545261","https://openalex.org/W2980950444","https://openalex.org/W2995356865","https://openalex.org/W2999995229","https://openalex.org/W3010777170","https://openalex.org/W3011744748","https://openalex.org/W3022039961","https://openalex.org/W3025473781","https://openalex.org/W3031464398","https://openalex.org/W3033044366","https://openalex.org/W3035337725","https://openalex.org/W3043243307","https://openalex.org/W3081228098","https://openalex.org/W3081463146","https://openalex.org/W3083066903","https://openalex.org/W3089356117","https://openalex.org/W3115346036","https://openalex.org/W3125605778","https://openalex.org/W3128764679","https://openalex.org/W3137749616","https://openalex.org/W3145728983","https://openalex.org/W3155281138","https://openalex.org/W3156704479","https://openalex.org/W3172153656","https://openalex.org/W6783264577"],"related_works":["https://openalex.org/W3005473267","https://openalex.org/W2947164722","https://openalex.org/W2119868897","https://openalex.org/W4319989607","https://openalex.org/W4395955498","https://openalex.org/W7161145317","https://openalex.org/W624227265","https://openalex.org/W2950416698","https://openalex.org/W2327769176","https://openalex.org/W2015393976"],"abstract_inverted_index":{"Traffic":[0],"accidents":[1],"are":[2,61,67,90,137,152,235,245],"caused":[3],"by":[4,143,175,285],"driver":[5,39,150,282],"fatigue":[6,42],"or":[7],"distraction":[8],"in":[9,22,35,72,85,216],"many":[10,287],"cases.":[11],"To":[12,79,102,223],"prevent":[13],"accidents,":[14],"several":[15],"low-cost":[16],"hypovigilance":[17],"(hypo-V)":[18],"systems":[19,284],"were":[20],"developed":[21],"the":[23,70,100,107,201,217,225,249,255,270],"past":[24],"based":[25,210,273],"on":[26,92,211,253,274],"a":[27,104,176,228,259],"multimodal-hybrid":[28],"(physiological":[29],"and":[30,41,51,75,97,116,119,139,146,165,184,214,276],"behavioral)":[31],"feature":[32,144],"set.":[33],"Similarly":[34],"this":[36],"paper,":[37],"real-time":[38],"inattention":[40],"(Hypo-Driver)":[43],"detection":[44,260],"system":[45,170,203,257,272],"is":[46,190,204],"proposed":[47],"through":[48],"multi-view":[49],"cameras":[50,89],"biosignal":[52],"sensors":[53,65],"to":[54,69,192,242,248],"extract":[55,193],"hybrid":[56],"features.":[57,195],"The":[58,149,237,265],"considered":[59],"features":[60,84,174,278],"derived":[62],"from":[63,232],"non-intrusive":[64],"that":[66,269],"related":[68],"changes":[71],"driving":[73],"behavior":[74],"visual":[76,82,161],"facial":[77,83],"expressions.":[78],"get":[80],"enhanced":[81],"uncontrolled":[86],"environment,":[87],"three":[88],"deployed":[91],"multiview":[93,277],"points":[94],"(0\u00b0,":[95],"45\u00b0,":[96],"90\u00b0)":[98],"of":[99,198,227,239,263],"drivers.":[101],"develop":[103],"Hypo-Driver":[105,202,240,256,271],"system,":[106,230,252],"physiological":[108,194],"signals":[109],"(electroencephalography":[110],"(EEG),":[111],"electrocardiography":[112],"(ECG),":[113],"electro-myography":[114],"(sEMG),":[115],"electrooculography":[117],"(EOG))":[118],"behavioral":[120,173],"information":[121],"(PERCLOS70-80-90%,":[122],"mouth":[123],"aspect":[124,128],"ratio":[125,129,135],"(MAR),":[126],"eye":[127],"(EAR),":[130],"blinking":[131],"frequency":[132],"(BF),":[133],"head-titled":[134],"(HT-R))":[136],"collected":[138],"pre-processed,":[140],"then":[141],"followed":[142],"selection":[145],"fusion":[147,197],"techniques.":[148],"behaviors":[151],"classified":[153,205],"into":[154,207],"five":[155,208],"stages":[156,209],"such":[157],"as":[158],"normal,":[159],"fatigue,":[160],"inattention,":[162,164],"cognitive":[163],"drowsy.":[166],"This":[167],"improved":[168],"hypo-Driver":[169,229],"utilized":[171],"trained":[172,212],"convolutional":[177],"neural":[178,182,219],"network":[179,183,220],"(CNNs),":[180],"recurrent":[181],"long":[185],"short-term":[186],"memory":[187],"(RNN-LSTM)":[188],"model":[189],"used":[191],"After":[196],"these":[199],"features,":[200],"hypo-V":[206],"layers":[213],"dropout-layer":[215],"deep-residual":[218],"(DRNN)":[221],"model.":[222],"test":[224],"performance":[226],"data":[231],"20":[233],"drivers":[234],"acquired.":[236],"results":[238,267],"compared":[241],"state-of-the-art":[243,250,281],"methods":[244],"presented.":[246],"Compared":[247],"Hypo-V":[251,283],"average,":[254],"achieved":[258],"accuracy":[261],"(AC)":[262],"96.5%.":[264],"obtained":[266],"indicate":[268],"multimodal":[275],"outperforms":[279],"other":[280],"handling":[286],"anomalies.":[288]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":7}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2021-11-08T00:00:00"}