{"id":"https://openalex.org/W4313035760","doi":"https://doi.org/10.1109/tits.2022.3230259","title":"Enabling Safe ITS: EEG-Based Microsleep Detection in VANETs","display_name":"Enabling Safe ITS: EEG-Based Microsleep Detection in VANETs","publication_year":2022,"publication_date":"2022-12-22","ids":{"openalex":"https://openalex.org/W4313035760","doi":"https://doi.org/10.1109/tits.2022.3230259"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3230259","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3230259","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","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":"https://openalex.org/A5014960719","display_name":"Amit Chougule","orcid":"https://orcid.org/0000-0002-7038-6944"},"institutions":[{"id":"https://openalex.org/I74796645","display_name":"Birla Institute of Technology and Science, Pilani","ror":"https://ror.org/001p3jz28","country_code":"IN","type":"education","lineage":["https://openalex.org/I74796645"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Amit Chougule","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, BITS–Pilani, Pilani, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, BITS–Pilani, Pilani, India","institution_ids":["https://openalex.org/I74796645"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112737571","display_name":"Jash Shah","orcid":"https://orcid.org/0009-0000-6427-587X"},"institutions":[{"id":"https://openalex.org/I74796645","display_name":"Birla Institute of Technology and Science, Pilani","ror":"https://ror.org/001p3jz28","country_code":"IN","type":"education","lineage":["https://openalex.org/I74796645"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jash Shah","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, BITS–Pilani, Pilani, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, BITS–Pilani, Pilani, India","institution_ids":["https://openalex.org/I74796645"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005020243","display_name":"Vinay Chamola","orcid":"https://orcid.org/0000-0002-6730-3060"},"institutions":[{"id":"https://openalex.org/I74796645","display_name":"Birla Institute of Technology and Science, Pilani","ror":"https://ror.org/001p3jz28","country_code":"IN","type":"education","lineage":["https://openalex.org/I74796645"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vinay Chamola","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, APPCAIR, BITS–Pilani, Pilani, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, APPCAIR, BITS–Pilani, Pilani, India","institution_ids":["https://openalex.org/I74796645"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059077090","display_name":"Salil S. Kanhere","orcid":"https://orcid.org/0000-0002-1835-3475"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Salil Kanhere","raw_affiliation_strings":["School of Computer Science and Engineering, UNSW, Sydney, ACT, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, UNSW, Sydney, ACT, Australia","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5014960719"],"corresponding_institution_ids":["https://openalex.org/I74796645"],"apc_list":null,"apc_paid":null,"fwci":1.2747,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.78879837,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"24","issue":"12","first_page":"15773","last_page":"15783"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"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":1.0,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9825999736785889,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.9825999736785889,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6394058465957642},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5822750926017761},{"id":"https://openalex.org/keywords/short-time-fourier-transform","display_name":"Short-time Fourier transform","score":0.5625513195991516},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.5590041875839233},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5288043022155762},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.5260515213012695},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45953086018562317},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.45136287808418274},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40218621492385864},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37840840220451355},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3555963635444641},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.2691550850868225},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15780740976333618},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.13465550541877747},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.0959138572216034}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6394058465957642},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5822750926017761},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.5625513195991516},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.5590041875839233},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5288043022155762},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.5260515213012695},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45953086018562317},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.45136287808418274},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40218621492385864},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37840840220451355},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3555963635444641},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.2691550850868225},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15780740976333618},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.13465550541877747},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.0959138572216034},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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:10.1109/tits.2022.3230259","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3230259","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W79430094","https://openalex.org/W1497474439","https://openalex.org/W1525254066","https://openalex.org/W1537044214","https://openalex.org/W1996021349","https://openalex.org/W1996369579","https://openalex.org/W2009755921","https://openalex.org/W2036959929","https://openalex.org/W2094784347","https://openalex.org/W2101567415","https://openalex.org/W2111766101","https://openalex.org/W2127864857","https://openalex.org/W2131774270","https://openalex.org/W2135280991","https://openalex.org/W2141220295","https://openalex.org/W2161491890","https://openalex.org/W2278108273","https://openalex.org/W2513213398","https://openalex.org/W2595838827","https://openalex.org/W2604096629","https://openalex.org/W2621385496","https://openalex.org/W2766809534","https://openalex.org/W2893892260","https://openalex.org/W2920016582","https://openalex.org/W2961770867","https://openalex.org/W2964204197","https://openalex.org/W2964801446","https://openalex.org/W2964959984","https://openalex.org/W3011886608","https://openalex.org/W3022066024","https://openalex.org/W3035374448","https://openalex.org/W3040939498","https://openalex.org/W3043229062","https://openalex.org/W3081708644","https://openalex.org/W3083053977","https://openalex.org/W3096813197","https://openalex.org/W3098250197","https://openalex.org/W3127909065","https://openalex.org/W3158818505","https://openalex.org/W3186684121","https://openalex.org/W3201785247","https://openalex.org/W3208850259","https://openalex.org/W3213425882","https://openalex.org/W4200601234","https://openalex.org/W4248699113","https://openalex.org/W4385245566","https://openalex.org/W6603225012","https://openalex.org/W6734665518","https://openalex.org/W6739150214","https://openalex.org/W6739901393","https://openalex.org/W6765424434","https://openalex.org/W6802706416"],"related_works":["https://openalex.org/W2120540196","https://openalex.org/W3095343173","https://openalex.org/W2381036744","https://openalex.org/W2288135719","https://openalex.org/W2323749021","https://openalex.org/W2533590149","https://openalex.org/W2901989338","https://openalex.org/W82005754","https://openalex.org/W2334448276","https://openalex.org/W3210733254"],"abstract_inverted_index":{"Researchers":[0],"nowadays":[1],"are":[2],"particularly":[3],"focusing":[4],"on":[5,163],"the":[6,15,53,80,95,100,133,158,164,185],"interpretation":[7],"of":[8,56,135,160],"EEG":[9,58,144],"signals":[10],"to":[11,31,38,50,52,151,193],"understand":[12],"and":[13,40,125,137,176,180],"exploit":[14],"information":[16],"they":[17],"provide":[18,75],"for":[19,79,148],"brain":[20],"activities.":[21],"Deep":[22],"learning":[23,119],"architectures":[24],"performing":[25],"sleep":[26,67],"staging":[27,68],"have":[28],"recently":[29],"grown":[30],"their":[32,36],"full":[33],"potential":[34],"with":[35,86,106],"ability":[37],"learn":[39,139],"interpret":[41],"highly":[42],"complex":[43],"mathematical":[44],"contexts.":[45],"This":[46],"has":[47],"been":[48],"catered":[49],"owing":[51],"increasing":[54],"availability":[55],"large":[57],"data":[59],"sets.":[60],"In":[61],"this":[62],"paper,":[63],"we":[64],"describe":[65],"how":[66],"differs":[69],"from":[70,132],"microsleep":[71,81,161],"prediction.":[72],"We":[73,112],"also":[74,113],"a":[76,116],"fresh":[77],"methodology":[78],"classification":[82],"job":[83],"that":[84,98,121],"works":[85],"even":[87],"less":[88],"training":[89,175],"data.":[90],"Our":[91],"proposed":[92],"model":[93,120,168],"exploits":[94],"attention-based":[96],"mechanism":[97],"clubs":[99],"advantages":[101],"available":[102],"in":[103,184],"Wavelet":[104],"transform":[105],"Short":[107],"Time":[108],"Fourier":[109],"Transform(STFT)":[110],"Spectrogram.":[111],"put":[114],"forward":[115],"robust":[117],"deep":[118],"contains":[122],"separate":[123],"\u201ctime-dependent\u201d":[124],"\u201ctime-independent\u201d":[126],"parts,":[127],"which":[128],"can":[129],"record":[130],"contexts":[131],"sequence":[134],"features":[136],"simultaneously":[138],"intra-epoch":[140],"relations.":[141],"A":[142],"single-electrode":[143],"signal":[145],"was":[146],"employed":[147],"our":[149,167],"analysis":[150],"accommodate":[152],"such":[153],"procedures\u2019":[154],"social":[155],"acceptance.":[156],"For":[157],"task":[159],"detection":[162],"MWT":[165],"dataset,":[166],"achieves":[169],"fairly":[170],"high":[171],"accuracy":[172],"rates":[173],"(92%":[174],"89.9%":[177],"testing":[178],"accuracy),":[179],"an":[181],"overall":[182],"improvement":[183],"kappa":[186],"value":[187],"by":[188],"\u2248":[189],"42%,":[190],"as":[191],"compared":[192],"prior":[194],"novel":[195],"approaches.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}