{"id":"https://openalex.org/W2755321226","doi":"https://doi.org/10.1109/embc.2017.8037855","title":"Prediction of microsleeps using pairwise joint entropy and mutual information between EEG channels","display_name":"Prediction of microsleeps using pairwise joint entropy and mutual information between EEG channels","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2755321226","doi":"https://doi.org/10.1109/embc.2017.8037855","mag":"2755321226","pmid":"https://pubmed.ncbi.nlm.nih.gov/29060896"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2017.8037855","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2017.8037855","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5109498503","display_name":"Abdul Baseer","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099107","display_name":"New Zealand Brain Research Institute","ror":"https://ror.org/01141nq92","country_code":"NZ","type":"facility","lineage":["https://openalex.org/I4210099107"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Abdul Baseer","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New Zealand Brain Research Institute, Christchurch, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New Zealand Brain Research Institute, Christchurch, New Zealand","institution_ids":["https://openalex.org/I4210099107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069800963","display_name":"Stephen J. Weddell","orcid":"https://orcid.org/0000-0002-2345-0077"},"institutions":[{"id":"https://openalex.org/I4210099107","display_name":"New Zealand Brain Research Institute","ror":"https://ror.org/01141nq92","country_code":"NZ","type":"facility","lineage":["https://openalex.org/I4210099107"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Stephen J. Weddell","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Christchurch Neurotechnology Research Programme, Christchurch, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Christchurch Neurotechnology Research Programme, Christchurch, New Zealand","institution_ids":["https://openalex.org/I4210099107"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088922632","display_name":"Richard D. Jones","orcid":"https://orcid.org/0000-0003-2287-3358"},"institutions":[{"id":"https://openalex.org/I4210099107","display_name":"New Zealand Brain Research Institute","ror":"https://ror.org/01141nq92","country_code":"NZ","type":"facility","lineage":["https://openalex.org/I4210099107"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Richard D. Jones","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Christchurch Neurotechnology Research Programme, Christchurch, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Christchurch Neurotechnology Research Programme, Christchurch, New Zealand","institution_ids":["https://openalex.org/I4210099107"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210099107"],"apc_list":null,"apc_paid":null,"fwci":0.9311,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.74089224,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"2017","issue":null,"first_page":"4495","last_page":"4498"},"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.9944999814033508,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.986299991607666,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.7621797323226929},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.7388816475868225},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6247508525848389},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.613053560256958},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5802793502807617},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.578246533870697},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5630703568458557},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5194917917251587},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.4853586256504059},{"id":"https://openalex.org/keywords/transfer-entropy","display_name":"Transfer entropy","score":0.4344249963760376},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4174463450908661},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40548160672187805},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3328610062599182},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.32018765807151794},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2723272144794464},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.21801215410232544}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7621797323226929},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.7388816475868225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6247508525848389},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.613053560256958},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5802793502807617},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.578246533870697},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5630703568458557},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5194917917251587},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.4853586256504059},{"id":"https://openalex.org/C182049051","wikidata":"https://www.wikidata.org/wiki/Q17147155","display_name":"Transfer entropy","level":3,"score":0.4344249963760376},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4174463450908661},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40548160672187805},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3328610062599182},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.32018765807151794},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2723272144794464},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.21801215410232544},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","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":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016002","descriptor_name":"Discriminant Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016002","descriptor_name":"Discriminant Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016002","descriptor_name":"Discriminant Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019277","descriptor_name":"Entropy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019277","descriptor_name":"Entropy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019277","descriptor_name":"Entropy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019540","descriptor_name":"Area Under Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019540","descriptor_name":"Area Under Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019540","descriptor_name":"Area Under Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc.2017.8037855","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2017.8037855","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:29060896","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29060896","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":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5899999737739563,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W167016754","https://openalex.org/W1522345630","https://openalex.org/W1987387046","https://openalex.org/W1994961181","https://openalex.org/W2025366179","https://openalex.org/W2036959929","https://openalex.org/W2062377220","https://openalex.org/W2089943482","https://openalex.org/W2090804142","https://openalex.org/W2101567415","https://openalex.org/W2101629127","https://openalex.org/W2127864857","https://openalex.org/W2154706222","https://openalex.org/W2294067654","https://openalex.org/W2533195094","https://openalex.org/W3144154667","https://openalex.org/W6606837198","https://openalex.org/W6631270133"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W2362114017","https://openalex.org/W1999647744","https://openalex.org/W3147024994","https://openalex.org/W2063246903","https://openalex.org/W2374055396","https://openalex.org/W1978302214","https://openalex.org/W2021817983","https://openalex.org/W3008559849","https://openalex.org/W2371177901"],"abstract_inverted_index":{"Microsleeps":[0],"are":[1],"involuntary":[2],"and":[3,24,47,75,83,142,149],"brief":[4],"instances":[5],"of":[6,9,12,95,102,121,144],"complete":[7],"loss":[8],"responsiveness,":[10],"typically":[11],"0.5-15":[13],"s":[14,133],"duration.":[15],"They":[16],"adversely":[17],"affect":[18],"performance":[19,120],"in":[20],"extended":[21],"attention-driven":[22],"jobs":[23],"can":[25],"be":[26],"fatal.":[27],"Our":[28],"aim":[29],"was":[30,68,115,135],"to":[31,54,70,117],"predict":[32],"microsleeps":[33],"from":[34,58],"16":[35],"channel":[36],"EEG":[37,59],"signals.":[38,60],"Two":[39],"information":[40,49],"theoretic":[41],"concepts":[42],"-":[43,50],"pairwise":[44],"joint":[45,73,153],"entropy":[46,74,154],"mutual":[48,76],"were":[51,81,86],"independently":[52],"used":[53,69],"continuously":[55],"extract":[56],"features":[57,80],"k-nearest":[61],"neighbor":[62],"(kNN)":[63],"with":[64,152],"k":[65],"=":[66],"3":[67],"calculate":[71],"both":[72],"information.":[77],"Highly":[78],"correlated":[79],"discarded":[82],"the":[84,100,103,119],"rest":[85],"ranked":[87],"using":[88,155],"Fisher":[89],"score":[90],"followed":[91],"by":[92],"an":[93],"average":[94],"3-fold":[96],"cross-validation":[97],"area":[98],"under":[99],"curve":[101],"receiver":[104],"operating":[105],"characteristic":[106],"(AUC":[107],"<sub":[108],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[109],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">ROC</sub>":[110],").":[111],"Leave-one-out":[112],"method":[113],"(LOOM)":[114],"performed":[116],"test":[118],"microsleep":[122],"prediction":[123,130],"system":[124],"on":[125],"independent":[126],"data.":[127],"The":[128],"best":[129],"for":[131],"0.25":[132],"ahead":[134],"AUCROC,":[136],"sensitivity,":[137],"precision,":[138],"geometric":[139],"mean":[140],"(GM),":[141],"\u03c6":[143],"0.93,":[145],"0.68,":[146],"0.33,":[147],"0.75,":[148],"0.38":[150],"respectively":[151],"single":[156],"linear":[157],"discriminant":[158],"analysis":[159],"(LDA)":[160],"classifier.":[161]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}