{"id":"https://openalex.org/W2615872479","doi":"https://doi.org/10.1109/thms.2017.2700631","title":"Nonlinear Dynamic Classification of Momentary Mental Workload Using Physiological Features and NARX-Model-Based Least-Squares Support Vector Machines","display_name":"Nonlinear Dynamic Classification of Momentary Mental Workload Using Physiological Features and NARX-Model-Based Least-Squares Support Vector Machines","publication_year":2017,"publication_date":"2017-05-18","ids":{"openalex":"https://openalex.org/W2615872479","doi":"https://doi.org/10.1109/thms.2017.2700631","mag":"2615872479"},"language":"en","primary_location":{"id":"doi:10.1109/thms.2017.2700631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/thms.2017.2700631","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"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 Human-Machine 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/A5101976123","display_name":"Jianhua Zhang","orcid":"https://orcid.org/0000-0001-8051-4746"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianhua Zhang","raw_affiliation_strings":["School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033657910","display_name":"Zhong Yin","orcid":"https://orcid.org/0000-0003-2013-4009"},"institutions":[{"id":"https://openalex.org/I148128674","display_name":"University of Shanghai for Science and Technology","ror":"https://ror.org/00ay9v204","country_code":"CN","type":"education","lineage":["https://openalex.org/I148128674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Yin","raw_affiliation_strings":["Engineering Research Center of Optical Instrument and System, Ministry of Education, Shanghai Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Engineering Research Center of Optical Instrument and System, Ministry of Education, Shanghai Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I148128674"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026577634","display_name":"Rubin Wang","orcid":"https://orcid.org/0000-0003-4110-2022"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rubin Wang","raw_affiliation_strings":["Institute of Cognitive Neurodynamics, East China University of Science and Technology, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Institute of Cognitive Neurodynamics, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101976123"],"corresponding_institution_ids":["https://openalex.org/I143593769"],"apc_list":null,"apc_paid":null,"fwci":2.2404,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.87887234,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"47","issue":"4","first_page":"536","last_page":"549"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998000264167786,"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":0.9998000264167786,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9889000058174133,"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/nonlinear-autoregressive-exogenous-model","display_name":"Nonlinear autoregressive exogenous model","score":0.8875531554222107},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.7351182699203491},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6261165738105774},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6018175482749939},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5922228693962097},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5390471816062927},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.503173291683197},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.497332364320755},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.45029163360595703},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"Multiclass classification","score":0.4112665057182312},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34030598402023315},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24876153469085693},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.21670114994049072},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11307975649833679}],"concepts":[{"id":"https://openalex.org/C42536954","wikidata":"https://www.wikidata.org/wiki/Q7049462","display_name":"Nonlinear autoregressive exogenous model","level":3,"score":0.8875531554222107},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7351182699203491},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6261165738105774},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6018175482749939},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5922228693962097},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5390471816062927},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.503173291683197},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.497332364320755},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.45029163360595703},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.4112665057182312},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34030598402023315},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24876153469085693},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.21670114994049072},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11307975649833679},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/thms.2017.2700631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/thms.2017.2700631","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"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 Human-Machine Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4534314435","display_name":null,"funder_award_id":"11232005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5981001170","display_name":null,"funder_award_id":"61075070","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324854","display_name":"University of Shanghai for Science and Technology","ror":"https://ror.org/00ay9v204"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W11277640","https://openalex.org/W139551720","https://openalex.org/W343027882","https://openalex.org/W1545407019","https://openalex.org/W1596717185","https://openalex.org/W1963488110","https://openalex.org/W1964535079","https://openalex.org/W1966351099","https://openalex.org/W1977132690","https://openalex.org/W1986438083","https://openalex.org/W1990609887","https://openalex.org/W1996635605","https://openalex.org/W1997528082","https://openalex.org/W2003392038","https://openalex.org/W2013795140","https://openalex.org/W2018598567","https://openalex.org/W2023133322","https://openalex.org/W2029517603","https://openalex.org/W2031590924","https://openalex.org/W2042819422","https://openalex.org/W2050892021","https://openalex.org/W2054886346","https://openalex.org/W2058132619","https://openalex.org/W2062823042","https://openalex.org/W2080209737","https://openalex.org/W2083264278","https://openalex.org/W2098537994","https://openalex.org/W2100930563","https://openalex.org/W2103408061","https://openalex.org/W2104780674","https://openalex.org/W2129503395","https://openalex.org/W2134652120","https://openalex.org/W2137570937","https://openalex.org/W2141224535","https://openalex.org/W2149904935","https://openalex.org/W2167298530","https://openalex.org/W2309281694","https://openalex.org/W4230674625","https://openalex.org/W4243048569","https://openalex.org/W6600494216","https://openalex.org/W6605751011","https://openalex.org/W6632812788"],"related_works":["https://openalex.org/W2606910468","https://openalex.org/W3116827148","https://openalex.org/W3120843198","https://openalex.org/W2154965898","https://openalex.org/W2036704594","https://openalex.org/W4226315710","https://openalex.org/W3083782034","https://openalex.org/W4287185323","https://openalex.org/W2117809914","https://openalex.org/W2995801509"],"abstract_inverted_index":{"This":[0],"paper":[1],"designs":[2],"a":[3,8,27,76,85,137,158],"pattern":[4],"classifier":[5],"based":[6],"on":[7],"Nonlinear":[9],"AutoRegressive":[10],"model":[11,67,80,156],"with":[12,136],"eXogenous":[13],"inputs":[14,42],"(NARX)":[15],"to":[16,43,74,157],"reveal":[17],"intricate":[18],"nonlinear":[19],"dynamical":[20],"correlation":[21],"between":[22,79],"mental":[23],"workload":[24],"(MWL)":[25],"of":[26,54,64,105,134,145,152],"human":[28],"operator":[29],"and":[30,36,82,98],"psychophysiological":[31],"features.":[32],"The":[33,62,90,110,142],"salient":[34],"electroencephalogram":[35],"electrocardiogram":[37],"features":[38,92],"were":[39,68,101],"selected":[40],"as":[41],"the":[44,65,115,128,150,153],"NARX":[45,66],"model,":[46],"whose":[47],"continuous":[48],"output":[49],"was":[50],"discretized":[51],"in":[52,103],"terms":[53,104],"five":[55],"MWL":[56,107,124],"classes":[57],"at":[58],"each":[59],"time":[60],"instant.":[61],"orders":[63],"determined":[69],"using":[70],"an":[71],"objective":[72],"function":[73],"achieve":[75],"good":[77],"tradeoff":[78],"accuracy":[81,126],"complexity":[83],"via":[84],"least-squares":[86],"support":[87],"vector":[88],"machine.":[89],"physiological":[91],"from":[93],"different":[94],"measurement":[95],"channels":[96],"(electrodes)":[97],"frequency":[99],"bands":[100],"compared":[102],"multiclass":[106],"classification":[108,111,125,132,146],"performance.":[109],"results":[112,144],"showed":[113],"that":[114],"locality":[116],"projection":[117],"preservation":[118],"technique":[119],"can":[120],"maintain":[121],"sufficiently":[122],"high":[123],"(with":[127],"highest":[129],"five-class":[130],"correct":[131],"rate":[133],"88%)":[135],"significantly":[138],"reduced":[139],"computational":[140],"complexity.":[141],"comparative":[143],"performance":[147],"also":[148],"demonstrated":[149],"superiority":[151],"proposed":[154],"dynamic":[155],"widely-used":[159],"static":[160],"model.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":1}],"updated_date":"2026-03-26T15:22:09.906841","created_date":"2025-10-10T00:00:00"}
