{"id":"https://openalex.org/W4389366322","doi":"https://doi.org/10.1145/3628797.3628941","title":"Deep Learning-based Prediction of Alertness and Drowsiness using EEG Signals","display_name":"Deep Learning-based Prediction of Alertness and Drowsiness using EEG Signals","publication_year":2023,"publication_date":"2023-12-06","ids":{"openalex":"https://openalex.org/W4389366322","doi":"https://doi.org/10.1145/3628797.3628941"},"language":"en","primary_location":{"id":"doi:10.1145/3628797.3628941","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3628797.3628941","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Symposium on Information and Communication Technology","raw_type":"proceedings-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/A5029379948","display_name":"Cong Thuan","orcid":"https://orcid.org/0000-0002-9950-1694"},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Cong Thuan Do","raw_affiliation_strings":["Hanoi University of Science and Technology, Viet Nam"],"raw_orcid":"https://orcid.org/0000-0002-9950-1694","affiliations":[{"raw_affiliation_string":"Hanoi University of Science and Technology, Viet Nam","institution_ids":["https://openalex.org/I94518387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101653251","display_name":"Anh Nam Le","orcid":"https://orcid.org/0009-0005-1407-7900"},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Anh Nam Le","raw_affiliation_strings":["Hanoi University of Science and Technology, Viet Nam"],"raw_orcid":"https://orcid.org/0009-0005-1407-7900","affiliations":[{"raw_affiliation_string":"Hanoi University of Science and Technology, Viet Nam","institution_ids":["https://openalex.org/I94518387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089409625","display_name":"V\u0103n \u0110\u1ee9c Nguy\u1ec5n","orcid":"https://orcid.org/0000-0003-1414-4032"},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Van Duc Nguyen","raw_affiliation_strings":["Hanoi University of Science and Technology, Viet Nam"],"raw_orcid":"https://orcid.org/0000-0003-1414-4032","affiliations":[{"raw_affiliation_string":"Hanoi University of Science and Technology, Viet Nam","institution_ids":["https://openalex.org/I94518387"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018288108","display_name":"Trinh Van Chien","orcid":"https://orcid.org/0000-0002-5675-8414"},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Van Chien Trinh","raw_affiliation_strings":["Hanoi University of Science and Technology, Viet Nam"],"raw_orcid":"https://orcid.org/0000-0002-5675-8414","affiliations":[{"raw_affiliation_string":"Hanoi University of Science and Technology, Viet Nam","institution_ids":["https://openalex.org/I94518387"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5029379948"],"corresponding_institution_ids":["https://openalex.org/I94518387"],"apc_list":null,"apc_paid":null,"fwci":0.3424,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59288616,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"533","last_page":"538"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9916999936103821,"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/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9830999970436096,"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/alertness","display_name":"Alertness","score":0.846933126449585},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7481512427330017},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6620283126831055},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6241718530654907},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6112027168273926},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4811619222164154},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.472089022397995},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4622357487678528},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.4548410475254059},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4244965612888336},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4184782803058624},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36521124839782715},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10682398080825806},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.08981132507324219}],"concepts":[{"id":"https://openalex.org/C200678441","wikidata":"https://www.wikidata.org/wiki/Q1423044","display_name":"Alertness","level":2,"score":0.846933126449585},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7481512427330017},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6620283126831055},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6241718530654907},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6112027168273926},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4811619222164154},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.472089022397995},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4622357487678528},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4548410475254059},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4244965612888336},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4184782803058624},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36521124839782715},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10682398080825806},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.08981132507324219},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3628797.3628941","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3628797.3628941","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Symposium on Information and Communication Technology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1983839088","https://openalex.org/W2028571532","https://openalex.org/W2064675550","https://openalex.org/W2076167842","https://openalex.org/W2076807218","https://openalex.org/W2079757204","https://openalex.org/W2093266575","https://openalex.org/W2133704610","https://openalex.org/W2606722458","https://openalex.org/W2965235999","https://openalex.org/W2971528351","https://openalex.org/W2991043486","https://openalex.org/W2995187799","https://openalex.org/W3032666109","https://openalex.org/W3035076484","https://openalex.org/W4220996532","https://openalex.org/W4307101487","https://openalex.org/W4384080511","https://openalex.org/W4385064726"],"related_works":["https://openalex.org/W2983142544","https://openalex.org/W2891059443","https://openalex.org/W4283822356","https://openalex.org/W4281663961","https://openalex.org/W1950940422","https://openalex.org/W3208888551","https://openalex.org/W4313561566","https://openalex.org/W2129146436","https://openalex.org/W3208386644","https://openalex.org/W2032507829"],"abstract_inverted_index":{"In":[0,33],"this":[1],"paper,":[2],"we":[3,37,56,76],"propose":[4],"to":[5,20,63,91,112],"apply":[6],"two":[7,104],"advanced":[8],"deep":[9,60],"learning":[10,61],"models,":[11,36],"comprising":[12],"Bidirectional":[13,53],"long":[14],"short-term":[15],"memory":[16],"(LSTM)":[17],"and":[18,48,67,80,118],"Transformer,":[19],"predict":[21],"the":[22,34,52,69,73,82,86,103,116],"alertness":[23,117],"or":[24],"drowsiness":[25,119],"of":[26,89,95,120],"individuals":[27],"via":[28],"utilizing":[29],"electroencephalogram":[30],"(EEG)":[31],"signals.":[32],"both":[35],"extract":[38],"some":[39],"features":[40,66,94],"from":[41],"brainwave":[42,65,97],"data":[43],"including":[44],"alpha,":[45],"beta,":[46],"delta,":[47],"theta":[49],"waves.":[50],"For":[51,72],"LSTM":[54],"model,":[55,75],"construct":[57],"a":[58],"four-layer":[59],"network":[62],"learn":[64],"classify":[68],"human":[70],"statuses.":[71],"Transformer":[74],"use":[77],"an":[78],"encoder":[79],"replace":[81],"position":[83],"encoding":[84],"with":[85],"vector":[87],"representation":[88],"time":[90],"capture":[92],"good":[93],"sequential":[96],"data.":[98],"Experimental":[99],"results":[100],"demonstrate":[101],"that":[102],"proposed":[105],"models":[106],"provide":[107],"very":[108],"high":[109],"accuracy,":[110],"up":[111],"99.55,":[113],"in":[114],"predicting":[115],"individuals.":[121]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}