{"id":"https://openalex.org/W2171980508","doi":"https://doi.org/10.1109/icbme.2013.6782224","title":"EEG-based emotion recognition using Recurrence Plot analysis and K nearest neighbor classifier","display_name":"EEG-based emotion recognition using Recurrence Plot analysis and K nearest neighbor classifier","publication_year":2013,"publication_date":"2013-12-01","ids":{"openalex":"https://openalex.org/W2171980508","doi":"https://doi.org/10.1109/icbme.2013.6782224","mag":"2171980508"},"language":"en","primary_location":{"id":"doi:10.1109/icbme.2013.6782224","doi":"https://doi.org/10.1109/icbme.2013.6782224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbme.2013.6782224","pdf_url":null,"source":{"id":"https://openalex.org/S7407087237","display_name":"National and International Iranian Conference on Biomedical Engineering (ICBME)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 20th Iranian Conference on Biomedical Engineering (ICBME)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5082964436","display_name":"Fatemeh Bahari","orcid":"https://orcid.org/0000-0002-9063-321X","observed_orcids":["https://orcid.org/0000-0002-9063-321X"]},"institutions":[{"id":"https://openalex.org/I158248296","display_name":"Amirkabir University of Technology","ror":"https://ror.org/04gzbav43","country_code":"IR","type":"education","lineage":["https://openalex.org/I158248296"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Fatemeh Bahari","raw_affiliation_strings":["Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I158248296"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072587929","display_name":"Amin Janghorbani","orcid":"https://orcid.org/0000-0001-6163-219X","observed_orcids":["https://orcid.org/0000-0001-6163-219X"]},"institutions":[{"id":"https://openalex.org/I158248296","display_name":"Amirkabir University of Technology","ror":"https://ror.org/04gzbav43","country_code":"IR","type":"education","lineage":["https://openalex.org/I158248296"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Amin Janghorbani","raw_affiliation_strings":["Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I158248296"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I158248296"],"apc_list":null,"apc_paid":null,"fwci":2.2679,"has_fulltext":false,"cited_by_count":80,"citation_normalized_percentile":{"value":0.89676113,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"228","last_page":"233"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.00019999999494757503,"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/T10057","display_name":"Face and Expression Recognition","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/eeg-based-emotion-recognition","display_name":"EEG-based emotion recognition","score":0.9490000009536743},{"id":"https://openalex.org/keywords/recurrence-plot-analysis","display_name":"recurrence plot analysis","score":0.9760000109672546},{"id":"https://openalex.org/keywords/nonlinear-feature-extraction","display_name":"nonlinear feature extraction","score":0.9070000052452087},{"id":"https://openalex.org/keywords/k-nearest-neighbors","display_name":"k-nearest neighbors","score":0.7770000100135803},{"id":"https://openalex.org/keywords/arousal","display_name":"arousal","score":0.5590000152587891},{"id":"https://openalex.org/keywords/valence","display_name":"valence","score":0.9980000257492065},{"id":"https://openalex.org/keywords/liking","display_name":"liking","score":0.9549999833106995},{"id":"https://openalex.org/keywords/power-spectral-features","display_name":"power spectral features","score":0.8240000009536743},{"id":"https://openalex.org/keywords/emotional-state-classification","display_name":"emotional state classification","score":0.6439999938011169}],"concepts":[{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.8016922473907471},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6919344067573547},{"id":"https://openalex.org/C36951298","wikidata":"https://www.wikidata.org/wiki/Q379784","display_name":"Arousal","level":2,"score":0.6850419044494629},{"id":"https://openalex.org/C168900304","wikidata":"https://www.wikidata.org/wiki/Q171407","display_name":"Valence (chemistry)","level":2,"score":0.6658704876899719},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6610347032546997},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6036911606788635},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5955265760421753},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.585679829120636},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.548983097076416},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5357868671417236},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4621942639350891},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2021106779575348},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.06665453314781189},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icbme.2013.6782224","doi":"https://doi.org/10.1109/icbme.2013.6782224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbme.2013.6782224","pdf_url":null,"source":{"id":"https://openalex.org/S7407087237","display_name":"National and International Iranian Conference on Biomedical Engineering (ICBME)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 20th Iranian Conference on Biomedical Engineering (ICBME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W617994985","https://openalex.org/W1549386224","https://openalex.org/W1873312687","https://openalex.org/W1978413235","https://openalex.org/W1984391316","https://openalex.org/W1993978186","https://openalex.org/W2002055708","https://openalex.org/W2026841692","https://openalex.org/W2040378199","https://openalex.org/W2054674198","https://openalex.org/W2067583143","https://openalex.org/W2081681829","https://openalex.org/W2091084672","https://openalex.org/W2107469377","https://openalex.org/W2131439016","https://openalex.org/W2136503609","https://openalex.org/W2138786254","https://openalex.org/W2140702793","https://openalex.org/W2149628368","https://openalex.org/W2150880403","https://openalex.org/W2154611638","https://openalex.org/W2156000847","https://openalex.org/W2170883741","https://openalex.org/W2171707680","https://openalex.org/W2339343773","https://openalex.org/W3010246639","https://openalex.org/W4236533540","https://openalex.org/W4251591997"],"related_works":["https://openalex.org/W2953214845","https://openalex.org/W2920125235","https://openalex.org/W2783519296","https://openalex.org/W4320737976","https://openalex.org/W2136503609","https://openalex.org/W4316039214","https://openalex.org/W2040171374","https://openalex.org/W2109773980","https://openalex.org/W2898698055","https://openalex.org/W7221500888"],"abstract_inverted_index":{"Electroencephalogram":[0],"(EEG)-based":[1],"emotion":[2,30],"recognition":[3],"has":[4],"been":[5],"a":[6,111],"rapidly":[7],"growing":[8],"field.":[9],"However,":[10],"accurate":[11],"and":[12,96,104],"sufficient":[13],"performance":[14,91],"rates":[15,92],"are":[16],"yet":[17],"to":[18,43,67,90],"be":[19],"obtained.":[20],"This":[21,48],"paper":[22],"presents":[23],"the":[24,32,72,83,108],"classification":[25],"of":[26,85,93,101,110],"EEG":[27],"correlates":[28],"on":[29,57,76],"using":[31],"relatively":[33],"new":[34],"non-linear":[35,46,112],"feature":[36,53,113,120],"extraction":[37,54,114,121],"method,":[38],"namely,":[39],"Recurrence":[40],"Plot":[41],"analysis":[42],"extract":[44],"thirteen":[45],"features.":[47],"method":[49,55,115],"is":[50,65],"compared":[51],"with":[52,82],"based":[56,75,119],"spectral":[58],"power":[59],"analysis.":[60],"The":[61],"K":[62],"nearest":[63],"neighbor":[64],"applied":[66],"classify":[68],"extracted":[69],"features":[70],"into":[71],"emotional":[73],"states":[74],"arousal-valence":[77],"(high/low":[78],"arousal,":[79],"valence)":[80],"plane":[81],"addition":[84],"liking":[86],"axis":[87],"(positive/negative).":[88],"Leading":[89],"58.05%,":[94],"64.56%":[95],"67.42%":[97],"for":[98],"3":[99],"classes":[100],"valence,":[102],"arousal":[103],"liking;":[105],"which":[106],"confirm":[107],"advantage":[109],"over":[116],"previous":[117],"frequency":[118],"techniques.":[122]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2}],"updated_date":"2026-10-29T09:56:32.521200","created_date":"2016-06-24T00:00:00"}