{"id":"https://openalex.org/W4226017002","doi":"https://doi.org/10.1109/tim.2022.3167793","title":"Nonlinear Analysis of Electroencephalogram Variability as a Measure of the Depth of Anesthesia","display_name":"Nonlinear Analysis of Electroencephalogram Variability as a Measure of the Depth of Anesthesia","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4226017002","doi":"https://doi.org/10.1109/tim.2022.3167793"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3167793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3167793","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5100400353","display_name":"Yi-Feng Chen","orcid":"https://orcid.org/0000-0002-2709-6036"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi-Feng Chen","raw_affiliation_strings":["Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-2709-6036","affiliations":[{"raw_affiliation_string":"Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040835437","display_name":"Shou\u2010Zen Fan","orcid":"https://orcid.org/0000-0002-6849-8453"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]},{"id":"https://openalex.org/I4210098629","display_name":"En Chu Kong Hospital","ror":"https://ror.org/015a6df35","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I4210098629"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shou-Zen Fan","raw_affiliation_strings":["Department of Anesthesiology, En Chu Kong Hospital, New Taipei City, Taiwan","School of Medicine, National Taiwan University, Taipei City, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-6849-8453","affiliations":[{"raw_affiliation_string":"Department of Anesthesiology, En Chu Kong Hospital, New Taipei City, Taiwan","institution_ids":["https://openalex.org/I4210098629"]},{"raw_affiliation_string":"School of Medicine, National Taiwan University, Taipei City, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091511508","display_name":"Maysam Abbod","orcid":"https://orcid.org/0000-0002-8515-7933"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Maysam F. Abbod","raw_affiliation_strings":["College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, U.K"],"raw_orcid":"https://orcid.org/0000-0002-8515-7933","affiliations":[{"raw_affiliation_string":"College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, U.K","institution_ids":["https://openalex.org/I59433898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027079662","display_name":"Jiann-Shing Shieh","orcid":"https://orcid.org/0000-0002-6407-5090"},"institutions":[{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jiann-Shing Shieh","raw_affiliation_strings":["Department of Mechanical Engineering, Yuan Ze University, Taoyuan, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-6407-5090","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Yuan Ze University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I99908691"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100381690","display_name":"Mingming Zhang","orcid":"https://orcid.org/0000-0001-8016-1856"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingming Zhang","raw_affiliation_strings":["Department of Biomedical Engineering, Shenzhen Key Laboratory of Smart Healthcare Engineering, Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-8016-1856","affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Shenzhen Key Laboratory of Smart Healthcare Engineering, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100400353"],"corresponding_institution_ids":["https://openalex.org/I3045169105"],"apc_list":null,"apc_paid":null,"fwci":1.4128,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.79775721,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9983000159263611,"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":0.9983000159263611,"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":0.9879000186920166,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9818000197410583,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.8303824067115784},{"id":"https://openalex.org/keywords/detrended-fluctuation-analysis","display_name":"Detrended fluctuation analysis","score":0.6853196024894714},{"id":"https://openalex.org/keywords/resampling","display_name":"Resampling","score":0.6568270325660706},{"id":"https://openalex.org/keywords/sample-entropy","display_name":"Sample entropy","score":0.5866252779960632},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5590888261795044},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5311383605003357},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5215989351272583},{"id":"https://openalex.org/keywords/jackknife-resampling","display_name":"Jackknife resampling","score":0.4936693608760834},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.48222672939300537},{"id":"https://openalex.org/keywords/approximate-entropy","display_name":"Approximate entropy","score":0.47776687145233154},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4640452265739441},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.45072320103645325},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.425533652305603},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3951480984687805},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32884782552719116},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2767086625099182},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.1796134114265442},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.13316255807876587}],"concepts":[{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.8303824067115784},{"id":"https://openalex.org/C21689155","wikidata":"https://www.wikidata.org/wiki/Q2451452","display_name":"Detrended fluctuation analysis","level":3,"score":0.6853196024894714},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.6568270325660706},{"id":"https://openalex.org/C66696666","wikidata":"https://www.wikidata.org/wiki/Q17105612","display_name":"Sample entropy","level":3,"score":0.5866252779960632},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5590888261795044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5311383605003357},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5215989351272583},{"id":"https://openalex.org/C81790035","wikidata":"https://www.wikidata.org/wiki/Q847158","display_name":"Jackknife resampling","level":3,"score":0.4936693608760834},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.48222672939300537},{"id":"https://openalex.org/C86859247","wikidata":"https://www.wikidata.org/wiki/Q4781760","display_name":"Approximate entropy","level":3,"score":0.47776687145233154},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4640452265739441},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.45072320103645325},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.425533652305603},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3951480984687805},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32884782552719116},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2767086625099182},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.1796134114265442},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.13316255807876587},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2022.3167793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3167793","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1128135838","display_name":null,"funder_award_id":"61903181","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G133040822","display_name":null,"funder_award_id":"MOST 110-2221-E-155-004-MY2","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1603307924","https://openalex.org/W1862394037","https://openalex.org/W1894217515","https://openalex.org/W1981757504","https://openalex.org/W1988565407","https://openalex.org/W1988881714","https://openalex.org/W1991033480","https://openalex.org/W2005509407","https://openalex.org/W2012558374","https://openalex.org/W2012640125","https://openalex.org/W2017286875","https://openalex.org/W2025742817","https://openalex.org/W2035479505","https://openalex.org/W2040147892","https://openalex.org/W2046255129","https://openalex.org/W2062487003","https://openalex.org/W2074396582","https://openalex.org/W2084444573","https://openalex.org/W2102096535","https://openalex.org/W2107560053","https://openalex.org/W2111772099","https://openalex.org/W2116106036","https://openalex.org/W2137778858","https://openalex.org/W2153230907","https://openalex.org/W2159171548","https://openalex.org/W2160097539","https://openalex.org/W2178228580","https://openalex.org/W2230943484","https://openalex.org/W2398905005","https://openalex.org/W2564119502","https://openalex.org/W2605126039","https://openalex.org/W2616875318","https://openalex.org/W2790348769","https://openalex.org/W2937971209","https://openalex.org/W2945976633","https://openalex.org/W2946909483","https://openalex.org/W2947596811","https://openalex.org/W2976849140","https://openalex.org/W2980835121","https://openalex.org/W3005165365","https://openalex.org/W3006585575","https://openalex.org/W3020649347","https://openalex.org/W3045704945","https://openalex.org/W3120191257","https://openalex.org/W3121928171","https://openalex.org/W3126085817","https://openalex.org/W3127674232","https://openalex.org/W3129527190","https://openalex.org/W3139176437","https://openalex.org/W3150889630","https://openalex.org/W3156672261"],"related_works":["https://openalex.org/W2413715820","https://openalex.org/W2165027852","https://openalex.org/W4291518329","https://openalex.org/W2168268740","https://openalex.org/W2802555865","https://openalex.org/W2030269677","https://openalex.org/W2997074122","https://openalex.org/W2090210347","https://openalex.org/W2151745193","https://openalex.org/W4375950240"],"abstract_inverted_index":{"Electroencephalogram":[0],"(EEG)":[1],"has":[2],"been":[3],"widely":[4],"used":[5,37,87,124,196,206],"to":[6,23,38,66,88,125,197,214],"measure":[7,180,215],"the":[8,13,43,49,68,94,98,109,188,199],"effect":[9],"of":[10,45,56,175,204],"anesthetics":[11],"on":[12],"central":[14],"nervous":[15],"system.":[16],"However,":[17],"EEG":[18,28,57,176],"signals":[19,202],"are":[20,36,58,64,86,115,195],"very":[21],"prone":[22],"artifacts.":[24],"In":[25,184],"this":[26],"article,":[27],"variability":[29],"(EEGV)":[30],"is":[31,122,187],"proposed,":[32],"and":[33,62,82,97,104,112,145,148,156,165,177],"nonlinear":[34,193],"models":[35],"analyze":[39,89,198],"EEGV":[40,69,160,178,201],"for":[41,129],"measuring":[42],"depth":[44],"anesthesia":[46,152],"(DoA).":[47],"First,":[48],"time":[50,70,190],"intervals":[51],"between":[52,101],"successive":[53],"local":[54],"maxima":[55],"extracted.":[59],"Then,":[60],"resampling":[61],"differentiation":[63],"applied":[65],"reconstruct":[67],"series.":[71],"Sample":[72],"entropy":[73,76],"(SampEn),":[74],"permutation":[75],"(PeEn),":[77],"detrended":[78],"fluctuation":[79],"analysis":[80,100],"(DFA),":[81],"Poincar\u00e9":[83],"plots":[84],"(PoPs)":[85],"EEGV.":[90],"The":[91,132,173],"area":[92],"under":[93],"curve":[95],"(AUC)":[96],"correlation":[99,166],"proposed":[102],"measures":[103],"conscious":[105],"level":[106],"indicated":[107],"by":[108],"bispectral":[110],"index":[111],"expert-labeled":[113],"data":[114],"investigated.":[116],"A":[117],"long":[118],"short-term":[119],"memory":[120],"network":[121],"further":[123],"combine":[126],"multiple":[127],"features":[128],"predicting":[130],"DoA.":[131,216],"results":[133],"from":[134,159,171],"59":[135],"patients":[136],"show":[137],"that":[138,191],"these":[139],"four":[140,192],"indices":[141],"can":[142,179],"differentiate":[143],"awake":[144],"unconscious":[146],"states":[147],"track":[149],"changes":[150],"in":[151],"states.":[153],"SampEn,":[154],"DFA,":[155],"PoP":[157],"derived":[158,170],"achieve":[161],"significantly":[162],"higher":[163],"AUCs":[164],"coefficients":[167],"than":[168],"those":[169],"EEG.":[172],"fusion":[174],"DoA":[181],"more":[182],"precisely.":[183],"summary,":[185],"it":[186],"first":[189],"methods":[194],"reconstructed":[200],"instead":[203],"traditionally":[205],"raw":[207],"EEG,":[208],"which":[209],"provides":[210],"a":[211],"robust":[212],"way":[213]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}