{"id":"https://openalex.org/W2615227392","doi":"https://doi.org/10.1109/cogsima.2017.7929581","title":"Electroencephalography (EEG) classification of cognitive tasks based on task engagement index","display_name":"Electroencephalography (EEG) classification of cognitive tasks based on task engagement index","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2615227392","doi":"https://doi.org/10.1109/cogsima.2017.7929581","mag":"2615227392"},"language":"en","primary_location":{"id":"doi:10.1109/cogsima.2017.7929581","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cogsima.2017.7929581","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","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/A5010590881","display_name":"Joseph Nuamah","orcid":"https://orcid.org/0000-0001-7172-0716"},"institutions":[{"id":"https://openalex.org/I35777872","display_name":"North Carolina Agricultural and Technical State University","ror":"https://ror.org/02aze4h65","country_code":"US","type":"education","lineage":["https://openalex.org/I35777872"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Joseph K. Nuamah","raw_affiliation_strings":["Industrial and Systems Engineering Department, North Carolina A&T State University, Greensboro, NC, USA"],"affiliations":[{"raw_affiliation_string":"Industrial and Systems Engineering Department, North Carolina A&T State University, Greensboro, NC, USA","institution_ids":["https://openalex.org/I35777872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046775743","display_name":"Younho Seong","orcid":"https://orcid.org/0000-0003-4807-8176"},"institutions":[{"id":"https://openalex.org/I35777872","display_name":"North Carolina Agricultural and Technical State University","ror":"https://ror.org/02aze4h65","country_code":"US","type":"education","lineage":["https://openalex.org/I35777872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Younho Seong","raw_affiliation_strings":["Industrial and Systems Engineering Department, North Carolina A&T State University, Greensboro, NC, USA"],"affiliations":[{"raw_affiliation_string":"Industrial and Systems Engineering Department, North Carolina A&T State University, Greensboro, NC, USA","institution_ids":["https://openalex.org/I35777872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101690399","display_name":"Sun Yi","orcid":"https://orcid.org/0000-0001-6375-3104"},"institutions":[{"id":"https://openalex.org/I35777872","display_name":"North Carolina Agricultural and Technical State University","ror":"https://ror.org/02aze4h65","country_code":"US","type":"education","lineage":["https://openalex.org/I35777872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sun Yi","raw_affiliation_strings":["Mechanical Engineering Department, North Carolina A&T State University, Greensboro, NC, USA"],"affiliations":[{"raw_affiliation_string":"Mechanical Engineering Department, North Carolina A&T State University, Greensboro, NC, USA","institution_ids":["https://openalex.org/I35777872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5010590881"],"corresponding_institution_ids":["https://openalex.org/I35777872"],"apc_list":null,"apc_paid":null,"fwci":1.189,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.77615041,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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/T10042","display_name":"Neural and Behavioral Psychology Studies","score":0.9710000157356262,"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/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9697999954223633,"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/electroencephalography","display_name":"Electroencephalography","score":0.8045076131820679},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6374207735061646},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6144956350326538},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.5757853388786316},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.569263219833374},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.5460392236709595},{"id":"https://openalex.org/keywords/psychophysiology","display_name":"Psychophysiology","score":0.5254615545272827},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.46614351868629456},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38514000177383423},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.38467827439308167},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34463727474212646},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34285983443260193},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3181285858154297},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.1477808654308319},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09446543455123901}],"concepts":[{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.8045076131820679},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6374207735061646},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6144956350326538},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.5757853388786316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.569263219833374},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.5460392236709595},{"id":"https://openalex.org/C23677625","wikidata":"https://www.wikidata.org/wiki/Q1428943","display_name":"Psychophysiology","level":2,"score":0.5254615545272827},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.46614351868629456},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38514000177383423},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.38467827439308167},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34463727474212646},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34285983443260193},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3181285858154297},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.1477808654308319},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09446543455123901},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cogsima.2017.7929581","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cogsima.2017.7929581","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.4000000059604645,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320337655","display_name":"Research, Development and Engineering Command","ror":"https://ror.org/02rdkx920"},{"id":"https://openalex.org/F4320338294","display_name":"Air Force Research Laboratory","ror":"https://ror.org/02e2egq70"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W55018851","https://openalex.org/W1974861501","https://openalex.org/W1979107521","https://openalex.org/W1980447390","https://openalex.org/W1988847151","https://openalex.org/W2008060633","https://openalex.org/W2013785827","https://openalex.org/W2017427280","https://openalex.org/W2024067166","https://openalex.org/W2029517603","https://openalex.org/W2043736971","https://openalex.org/W2078446903","https://openalex.org/W2104780674","https://openalex.org/W2128495200","https://openalex.org/W2148834573","https://openalex.org/W2156849207","https://openalex.org/W2168468928","https://openalex.org/W2263183093","https://openalex.org/W2308827480","https://openalex.org/W2329821500","https://openalex.org/W2403001746","https://openalex.org/W2487581775","https://openalex.org/W2492338201","https://openalex.org/W2544487422","https://openalex.org/W2546667215","https://openalex.org/W2572840805","https://openalex.org/W4239548232","https://openalex.org/W6602235344","https://openalex.org/W6647265823","https://openalex.org/W6731769324"],"related_works":["https://openalex.org/W4232492598","https://openalex.org/W4214763677","https://openalex.org/W1601370735","https://openalex.org/W4221128511","https://openalex.org/W2087086293","https://openalex.org/W2894173309","https://openalex.org/W4387932263","https://openalex.org/W2098962763","https://openalex.org/W2371065793","https://openalex.org/W2157746493"],"abstract_inverted_index":{"The":[0,155,166],"application":[1,56],"of":[2,28,50,63,108,129,152,179,189],"autonomous":[3,30,35],"systems":[4,31,36],"is":[5,11,88],"on":[6,46],"an":[7,47,68,119],"increase,":[8],"and":[9,20,54,75,127],"there":[10],"the":[12,16,29,34,61,80,97,106,160,187,190],"need":[13],"to":[14,66,110,118,124,145],"optimize":[15],"fit":[17],"between":[18],"humans":[19],"these":[21],"systems.":[22],"While":[23],"operators":[24,69],"must":[25,37],"be":[26,184],"aware":[27],"dynamic":[32],"behaviors,":[33],"in":[38,171],"turn":[39],"base":[40],"their":[41],"operations,":[42],"among":[43],"other":[44],"things,":[45],"ongoing":[48],"knowledge":[49],"operators'":[51],"cognitive":[52,172],"state,":[53],"its":[55],"domain.":[57],"Psychophysiology":[58],"allows":[59],"for":[60,92,150],"use":[62,188],"physiological":[64,77],"measurements":[65],"understand":[67],"behavior":[70],"by":[71,141],"noninvasively":[72],"recording":[73],"peripheral":[74],"central":[76],"changes":[78],"while":[79],"operator":[81],"behaves":[82],"under":[83],"controlled":[84],"conditions.":[85],"Electroencephalography":[86],"(EEG)":[87],"a":[89],"psychophysiological":[90],"technique":[91],"studying":[93],"brain":[94],"activation.":[95],"In":[96],"present":[98],"study,":[99],"EEG":[100],"task":[101,173,191],"engagement":[102,192],"index,":[103],"defined":[104],"as":[105,116],"ratio":[107],"beta":[109],"(alpha":[111],"+":[112],"theta),":[113],"are":[114],"used":[115],"inputs":[117],"artificial":[120],"neural":[121],"network":[122],"(ANN)":[123],"allow":[125],"identification":[126],"classification":[128,157],"mental":[130,148,180],"engagement.":[131],"Six":[132],"separate":[133],"feedforward":[134],"ANN":[135],"with":[136],"single":[137],"hidden":[138],"layer":[139],"trained":[140],"backpropagation":[142],"were":[143],"designed":[144],"classify":[146],"five":[147],"tasks":[149],"each":[151],"six":[153,161],"participants.":[154],"average":[156],"accuracy":[158],"across":[159],"participants":[162],"was":[163],"88.67":[164],"%.":[165],"results":[167],"show":[168],"that":[169],"differences":[170],"demand":[174],"do":[175],"elicit":[176],"different":[177],"degrees":[178],"engagement,":[181],"which":[182],"can":[183],"measured":[185],"through":[186],"index.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}
