{"id":"https://openalex.org/W2998177232","doi":"https://doi.org/10.1109/ictc46691.2019.8939824","title":"Finding and evaluating suitable contents to recognize depression based on neuro-fuzzy algorithm","display_name":"Finding and evaluating suitable contents to recognize depression based on neuro-fuzzy algorithm","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2998177232","doi":"https://doi.org/10.1109/ictc46691.2019.8939824","mag":"2998177232"},"language":"en","primary_location":{"id":"doi:10.1109/ictc46691.2019.8939824","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc46691.2019.8939824","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Information and Communication Technology Convergence (ICTC)","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/A5100630438","display_name":"Minwoo Kim","orcid":"https://orcid.org/0000-0002-7840-1416"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Minwoo Kim","raw_affiliation_strings":["Department of Computer Engineering, Gachon University Seongname-si, Gyeonggi-do, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Gachon University Seongname-si, Gyeonggi-do, South Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102803771","display_name":"Joon S. Lim","orcid":"https://orcid.org/0000-0002-0018-946X"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Joon S. Lim","raw_affiliation_strings":["Department of Computer Engineering, Gachon University Seongname-si, Gyeonggi-do, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Gachon University Seongname-si, Gyeonggi-do, South Korea","institution_ids":["https://openalex.org/I12832649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100630438"],"corresponding_institution_ids":["https://openalex.org/I12832649"],"apc_list":null,"apc_paid":null,"fwci":0.3286,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.6684689,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2019","issue":null,"first_page":"478","last_page":"483"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9994000196456909,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9975000023841858,"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":0.9952999949455261,"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/heart-rate-variability","display_name":"Heart rate variability","score":0.6290198564529419},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.573174774646759},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5378936529159546},{"id":"https://openalex.org/keywords/content","display_name":"Content (measure theory)","score":0.5141749382019043},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5083047747612},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5013535022735596},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4875037372112274},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4808374345302582},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.4794803559780121},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4643927216529846},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45833638310432434},{"id":"https://openalex.org/keywords/meditation","display_name":"Meditation","score":0.4444602131843567},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4149298667907715},{"id":"https://openalex.org/keywords/friedman-test","display_name":"Friedman test","score":0.4103090167045593},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35946953296661377},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.340162992477417},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22427520155906677},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.14844685792922974},{"id":"https://openalex.org/keywords/heart-rate","display_name":"Heart rate","score":0.10634157061576843},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.09386703372001648}],"concepts":[{"id":"https://openalex.org/C71635504","wikidata":"https://www.wikidata.org/wiki/Q933954","display_name":"Heart rate variability","level":4,"score":0.6290198564529419},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.573174774646759},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5378936529159546},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.5141749382019043},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5083047747612},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5013535022735596},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4875037372112274},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4808374345302582},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.4794803559780121},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4643927216529846},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45833638310432434},{"id":"https://openalex.org/C521822307","wikidata":"https://www.wikidata.org/wiki/Q108458","display_name":"Meditation","level":2,"score":0.4444602131843567},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4149298667907715},{"id":"https://openalex.org/C160710788","wikidata":"https://www.wikidata.org/wiki/Q1457633","display_name":"Friedman test","level":3,"score":0.4103090167045593},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35946953296661377},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.340162992477417},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22427520155906677},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.14844685792922974},{"id":"https://openalex.org/C2777953023","wikidata":"https://www.wikidata.org/wiki/Q1073121","display_name":"Heart rate","level":3,"score":0.10634157061576843},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09386703372001648},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ictc46691.2019.8939824","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc46691.2019.8939824","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"},{"id":"mag:3009983611","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002274321832935","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1549711046","https://openalex.org/W2016724698","https://openalex.org/W2054421446","https://openalex.org/W2084908308","https://openalex.org/W2098930218","https://openalex.org/W2133589238","https://openalex.org/W2144722423","https://openalex.org/W2147095737","https://openalex.org/W2170332928","https://openalex.org/W2591383857","https://openalex.org/W2755951867"],"related_works":["https://openalex.org/W3017994638","https://openalex.org/W3214577301","https://openalex.org/W2995989211","https://openalex.org/W2751473014","https://openalex.org/W2941663400","https://openalex.org/W2562037482","https://openalex.org/W2965659963","https://openalex.org/W2987761576","https://openalex.org/W2808522083","https://openalex.org/W3037311895","https://openalex.org/W2885322397","https://openalex.org/W1823928250","https://openalex.org/W2126719297","https://openalex.org/W3114943056","https://openalex.org/W2788029111","https://openalex.org/W3185344918","https://openalex.org/W1982149561","https://openalex.org/W136167008","https://openalex.org/W2181848729","https://openalex.org/W3193300093"],"abstract_inverted_index":{"Using":[0],"heart":[1],"rate":[2],"variability":[3],"(HRV)":[4],"and":[5,22,79,162,192],"a":[6,116,147],"neuro-fuzzy":[7,94,178],"algorithm,":[8],"this":[9],"experiment":[10],"determined":[11],"certain":[12],"content":[13,28,52],"that":[14],"show":[15],"the":[16,27,32,42,51,61,93,100,106,122,126,144,149,159,166,170,177,182,187],"largest":[17],"difference":[18],"between":[19],"depression":[20,33,160],"patients":[21,34,161],"normal":[23,37,163],"subjects.":[24,164],"To":[25],"investigate":[26],"environment":[29],"in":[30,92],"which":[31],"an":[35],"d":[36],"subjects":[38,47],"were":[39,155],"effectively":[40],"classified,":[41],"HRV":[43,108],"extracted":[44,65],"from":[45,105],"test":[46,173],"was":[48,96,133,190,195],"divided":[49,62],"by":[50,68,120,180],"of":[53,118,125,137,140,168,184],"multimodal":[54],"affective":[55],"contents":[56,128,139,154],"(MAC)":[57],"stimulation":[58],"scenarios.":[59],"From":[60],"HRV,":[63],"we":[64],"22":[66,107],"features":[67,101,109,124],"using":[69,121,181],"frequency":[70],"domain":[71,74],"methods,":[72,75,78],"time":[73],"wavelet":[76],"transformed":[77],"Poincar\u00e9":[80],"transform":[81],"methods.":[82],"A":[83],"feature":[84],"selection":[85],"method,":[86],"non-overlap":[87],"area":[88],"distribution":[89],"measurement,":[90],"provided":[91],"algorithm":[95,179],"used":[97],"to":[98,111],"select":[99],"with":[102,176],"high":[103],"importance":[104],"corresponding":[110],"their":[112],"respective":[113,127],"contents.":[114],"As":[115],"result":[117],"learning":[119],"selected":[123],"as":[129],"input":[130],"values,":[131],"it":[132],"found":[134],"that,":[135],"out":[136],"14":[138],"MAC":[141],"simulation":[142],"scenarios,":[143],"Funniest":[145],"Video":[146],"nd":[148],"Meditation":[150],"&":[151],"Nature":[152],"Sound":[153],"effective":[156],"for":[157],"classifying":[158],"In":[165],"results":[167],"conducting":[169],"leave-one-out":[171],"cross-validation":[172],"100":[174],"times":[175],"signals":[183],"two":[185],"contents,":[186],"mean":[188],"accuracy":[189,194],"86.6%":[191],"maximum":[193],"86.":[196],"9%.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-20T08:49:12.498775","created_date":"2025-10-10T00:00:00"}
