{"id":"https://openalex.org/W4387186839","doi":"https://doi.org/10.3390/s23198171","title":"Deep Learning for Detecting Multi-Level Driver Fatigue Using Physiological Signals: A Comprehensive Approach","display_name":"Deep Learning for Detecting Multi-Level Driver Fatigue Using Physiological Signals: A Comprehensive Approach","publication_year":2023,"publication_date":"2023-09-29","ids":{"openalex":"https://openalex.org/W4387186839","doi":"https://doi.org/10.3390/s23198171","pmid":"https://pubmed.ncbi.nlm.nih.gov/37837001"},"language":"en","primary_location":{"id":"doi:10.3390/s23198171","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23198171","pdf_url":"https://www.mdpi.com/1424-8220/23/19/8171/pdf?version=1695983985","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/19/8171/pdf?version=1695983985","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058495552","display_name":"Mohammad Peivandi","orcid":"https://orcid.org/0000-0001-8707-1693"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammad Peivandi","raw_affiliation_strings":["Department of Biomedical Engineering, Wayne State University, Detroit, MI 48202, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Wayne State University, Detroit, MI 48202, USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111154683","display_name":"Sevda Zafarmandi Ardabili","orcid":null},"institutions":[{"id":"https://openalex.org/I178169726","display_name":"Southern Methodist University","ror":"https://ror.org/042tdr378","country_code":"US","type":"education","lineage":["https://openalex.org/I178169726"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sevda Zafarmandi Ardabili","raw_affiliation_strings":["Electrical and Computer Engineering Department, Southern Methodist University, Dallas, TX 75205, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, Southern Methodist University, Dallas, TX 75205, USA","institution_ids":["https://openalex.org/I178169726"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054320766","display_name":"Sobhan Sheykhivand","orcid":"https://orcid.org/0000-0002-2275-8133"},"institutions":[{"id":"https://openalex.org/I1300409581","display_name":"University of Bonab","ror":"https://ror.org/01app8660","country_code":"IR","type":"education","lineage":["https://openalex.org/I1300409581"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Sobhan Sheykhivand","raw_affiliation_strings":["Department of Biomedical Engineering, University of Bonab, Bonab 55517-61167, Iran"],"raw_orcid":"https://orcid.org/0000-0002-2275-8133","affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, University of Bonab, Bonab 55517-61167, Iran","institution_ids":["https://openalex.org/I1300409581"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063416360","display_name":"Sebelan Danishvar","orcid":"https://orcid.org/0000-0002-8258-0437"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Sebelan Danishvar","raw_affiliation_strings":["College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge UB8 3PH, UK"],"raw_orcid":"https://orcid.org/0000-0002-8258-0437","affiliations":[{"raw_affiliation_string":"College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge UB8 3PH, UK","institution_ids":["https://openalex.org/I59433898"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5063416360"],"corresponding_institution_ids":["https://openalex.org/I59433898"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":4.6252,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.95663912,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"23","issue":"19","first_page":"8171","last_page":"8171"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9916999936103821,"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":0.9916999936103821,"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/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9894000291824341,"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/T14011","display_name":"Elevator Systems and Control","score":0.957099974155426,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/computer-science","display_name":"Computer science","score":0.6017907857894897},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5782402753829956},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5365429520606995},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45965614914894104},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4209071099758148},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4098955988883972},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35096386075019836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6017907857894897},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5782402753829956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5365429520606995},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45965614914894104},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4209071099758148},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4098955988883972},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35096386075019836}],"mesh":[{"descriptor_ui":"D000063","descriptor_name":"Accidents, Traffic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000063","descriptor_name":"Accidents, Traffic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000063","descriptor_name":"Accidents, Traffic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001334","descriptor_name":"Automobile Driving","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001334","descriptor_name":"Automobile Driving","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001334","descriptor_name":"Automobile Driving","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005221","descriptor_name":"Fatigue","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D005221","descriptor_name":"Fatigue","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D005221","descriptor_name":"Fatigue","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":6,"locations":[{"id":"doi:10.3390/s23198171","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23198171","pdf_url":"https://www.mdpi.com/1424-8220/23/19/8171/pdf?version=1695983985","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:37837001","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37837001","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:bura.brunel.ac.uk:2438/27615","is_oa":true,"landing_page_url":"https://bura.brunel.ac.uk/handle/2438/27615","pdf_url":"http://bura.brunel.ac.uk/bitstream/2438/27615/1/FullText.pdf","source":{"id":"https://openalex.org/S4306401473","display_name":"Brunel University Research Archive (BURA) (Brunel University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59433898","host_organization_name":"Brunel University of London","host_organization_lineage":["https://openalex.org/I59433898"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:10574985","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10574985","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10574985/pdf/sensors-23-08171.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:adc0095c887e4adf9c3293b4f735d9c5","is_oa":true,"landing_page_url":"https://doaj.org/article/adc0095c887e4adf9c3293b4f735d9c5","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 23, Iss 19, p 8171 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/23/19/8171/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s23198171","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s23198171","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23198171","pdf_url":"https://www.mdpi.com/1424-8220/23/19/8171/pdf?version=1695983985","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387186839.pdf"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W2064126425","https://openalex.org/W2118376908","https://openalex.org/W2129225251","https://openalex.org/W2791136703","https://openalex.org/W2791603829","https://openalex.org/W2918092040","https://openalex.org/W2922416509","https://openalex.org/W2978631110","https://openalex.org/W2996303202","https://openalex.org/W3027380314","https://openalex.org/W3045665366","https://openalex.org/W3096831136","https://openalex.org/W3172040767","https://openalex.org/W3214818997","https://openalex.org/W4200497959","https://openalex.org/W4214839300","https://openalex.org/W4221029594","https://openalex.org/W4226474955","https://openalex.org/W4281740910","https://openalex.org/W4283326279","https://openalex.org/W4283740001","https://openalex.org/W4285044434","https://openalex.org/W4290987575","https://openalex.org/W4297053023","https://openalex.org/W4309852328","https://openalex.org/W4313479389","https://openalex.org/W4313593149","https://openalex.org/W4317620998","https://openalex.org/W4318954127","https://openalex.org/W4319015555","https://openalex.org/W4321600647","https://openalex.org/W4323318609","https://openalex.org/W4365479680","https://openalex.org/W4376869160","https://openalex.org/W4377221023","https://openalex.org/W4378611693","https://openalex.org/W4380047987","https://openalex.org/W4385342187","https://openalex.org/W6749584015","https://openalex.org/W6839129206","https://openalex.org/W6849233895","https://openalex.org/W6945105524"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W4380075502"],"abstract_inverted_index":{"A":[0,41,91],"large":[1],"share":[2],"of":[3,113,122,132,144,179,192],"traffic":[4],"accidents":[5],"is":[6],"related":[7],"to":[8,21,36,76,106,195],"driver":[9,39,43,180,193],"fatigue.":[10,40,114],"In":[11,26,115],"recent":[12],"years,":[13],"many":[14],"studies":[15],"have":[16],"been":[17],"organized":[18],"in":[19,34,152,189],"order":[20,35],"diagnose":[22],"and":[23,55,70,99,109,138,141,159,164],"warn":[24,196],"drivers.":[25,197],"this":[27,61],"research,":[28],"a":[29],"new":[30],"approach":[31],"was":[32,58,66,84,104,146],"presented":[33],"detect":[37],"multi-level":[38,42],"tiredness":[44],"diagnostic":[45],"database":[46],"based":[47,87,94],"on":[48,88,95],"physiological":[49],"signals":[50,73],"including":[51],"ECG,":[52],"EEG,":[53],"EMG,":[54],"respiratory":[56],"effort":[57],"developed":[59],"for":[60,68],"aim.":[62],"The":[63,148],"EEG":[64],"signal":[65],"used":[67,75,130],"processing":[69],"other":[71],"recorded":[72],"were":[74,129,161],"confirm":[77],"the":[78,116,120,142,153,168],"driver's":[79],"fatigue":[80,83,181,194],"so":[81],"that":[82],"not":[85],"confirmed":[86],"self-report":[89],"questionnaires.":[90],"customized":[92,117],"architecture":[93],"adversarial":[96],"generative":[97],"networks":[98,102],"convolutional":[100],"neural":[101],"(end-to-end)":[103],"utilized":[105],"select/extract":[107],"features":[108],"classify":[110],"different":[111],"levels":[112,178],"architecture,":[118],"with":[119,182],"objective":[121],"eliminating":[123],"uncertainty,":[124],"type":[125],"2":[126],"fuzzy":[127],"sets":[128],"instead":[131],"activation":[133],"functions":[134],"such":[135],"as":[136],"Relu":[137],"Leaky":[139],"Relu,":[140],"performance":[143],"each":[145],"investigated.":[147],"final":[149],"accuracy":[150],"obtained":[151],"three":[154],"scenarios":[155],"considered,":[156],"two-level,":[157],"three-level,":[158],"five-level,":[160],"96.8%,":[162],"95.1%,":[163],"89.1%,":[165],"respectively.":[166],"Given":[167],"suggested":[169],"model's":[170],"optimal":[171],"performance,":[172],"which":[173],"can":[174,186],"identify":[175],"five":[176],"various":[177],"high":[183],"accuracy,":[184],"it":[185],"be":[187],"employed":[188],"practical":[190],"applications":[191]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3}],"updated_date":"2026-06-05T09:01:59.212387","created_date":"2025-10-10T00:00:00"}
