{"id":"https://openalex.org/W2917094047","doi":"https://doi.org/10.1109/taffc.2019.2901673","title":"Feature Extraction and Selection for Emotion Recognition from Electrodermal Activity","display_name":"Feature Extraction and Selection for Emotion Recognition from Electrodermal Activity","publication_year":2019,"publication_date":"2019-02-26","ids":{"openalex":"https://openalex.org/W2917094047","doi":"https://doi.org/10.1109/taffc.2019.2901673","mag":"2917094047"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2019.2901673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2019.2901673","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"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 Affective Computing","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/A5068933672","display_name":"Jainendra Shukla","orcid":"https://orcid.org/0000-0002-6526-0087"},"institutions":[{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Jainendra Shukla","raw_affiliation_strings":["Department of Computer Science and Engineering, Indraprastha Institute of Information Technology Delhi (IIIT-D), New Delhi, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indraprastha Institute of Information Technology Delhi (IIIT-D), New Delhi, India","institution_ids":["https://openalex.org/I119939252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004637915","display_name":"Miguel Barreda-\u00c1ngeles","orcid":"https://orcid.org/0000-0002-5056-7633"},"institutions":[{"id":"https://openalex.org/I4210087295","display_name":"Centre Tecnologic de Telecomunicacions de Catalunya","ror":"https://ror.org/001cwea56","country_code":"ES","type":"nonprofit","lineage":["https://openalex.org/I4210087295","https://openalex.org/I4387153040"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Miguel Barreda-Angeles","raw_affiliation_strings":["Eurecat, Centre Tecnol\u00f2gic de Catalunya, Barcelona, Spain"],"affiliations":[{"raw_affiliation_string":"Eurecat, Centre Tecnol\u00f2gic de Catalunya, Barcelona, Spain","institution_ids":["https://openalex.org/I4210087295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000913157","display_name":"Joan Guix Oliver","orcid":"https://orcid.org/0000-0002-7388-3428"},"institutions":[{"id":"https://openalex.org/I4210093282","display_name":"Institut de Rob\u00f2tica i Inform\u00e0tica Industrial","ror":"https://ror.org/00mcdyn90","country_code":"ES","type":"facility","lineage":["https://openalex.org/I134820265","https://openalex.org/I4210093282","https://openalex.org/I9617848"]},{"id":"https://openalex.org/I55952717","display_name":"Universitat Rovira i Virgili","ror":"https://ror.org/00g5sqv46","country_code":"ES","type":"education","lineage":["https://openalex.org/I55952717"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Joan Oliver","raw_affiliation_strings":["Instituto de Rob\u00f3tica para la Dependencia, Sitges, Barcelona, Spain","Intelligent Robotics and Computer Vision Group, Universitat Rovira i Virgili, Tarragona, Spain"],"affiliations":[{"raw_affiliation_string":"Instituto de Rob\u00f3tica para la Dependencia, Sitges, Barcelona, Spain","institution_ids":["https://openalex.org/I4210093282"]},{"raw_affiliation_string":"Intelligent Robotics and Computer Vision Group, Universitat Rovira i Virgili, Tarragona, Spain","institution_ids":["https://openalex.org/I55952717"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076307665","display_name":"G. C. Nandi","orcid":"https://orcid.org/0000-0001-9417-4439"},"institutions":[{"id":"https://openalex.org/I26072440","display_name":"Indian Institute of Information Technology Allahabad","ror":"https://ror.org/03rgjt374","country_code":"IN","type":"education","lineage":["https://openalex.org/I26072440"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"G. C. Nandi","raw_affiliation_strings":["Department of Robotics & Artificial Intelligence, Indian Institute of Information Technology Allahabad (IIIT-A), Allahabad, Uttar Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of Robotics & Artificial Intelligence, Indian Institute of Information Technology Allahabad (IIIT-A), Allahabad, Uttar Pradesh, India","institution_ids":["https://openalex.org/I26072440"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004665770","display_name":"Dom\u00e8nec Puig","orcid":"https://orcid.org/0000-0002-0562-4205"},"institutions":[{"id":"https://openalex.org/I55952717","display_name":"Universitat Rovira i Virgili","ror":"https://ror.org/00g5sqv46","country_code":"ES","type":"education","lineage":["https://openalex.org/I55952717"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Domenec Puig","raw_affiliation_strings":["Intelligent Robotics and Computer Vision Group, Universitat Rovira i Virgili, Tarragona, Spain"],"affiliations":[{"raw_affiliation_string":"Intelligent Robotics and Computer Vision Group, Universitat Rovira i Virgili, Tarragona, Spain","institution_ids":["https://openalex.org/I55952717"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5068933672"],"corresponding_institution_ids":["https://openalex.org/I119939252"],"apc_list":null,"apc_paid":null,"fwci":17.9677,"has_fulltext":false,"cited_by_count":236,"citation_normalized_percentile":{"value":0.99510849,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"12","issue":"4","first_page":"857","last_page":"869"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9979000091552734,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9721999764442444,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7324681282043457},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6327290534973145},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6246739625930786},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.6008788347244263},{"id":"https://openalex.org/keywords/valence","display_name":"Valence (chemistry)","score":0.5777480602264404},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5661159753799438},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5570142865180969},{"id":"https://openalex.org/keywords/arousal","display_name":"Arousal","score":0.547730565071106},{"id":"https://openalex.org/keywords/conditional-mutual-information","display_name":"Conditional mutual information","score":0.5141680240631104},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.46397098898887634},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.4586044251918793},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4528827965259552},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4457618296146393},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.4380190372467041},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3321239948272705},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.24768859148025513}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7324681282043457},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6327290534973145},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6246739625930786},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.6008788347244263},{"id":"https://openalex.org/C168900304","wikidata":"https://www.wikidata.org/wiki/Q171407","display_name":"Valence (chemistry)","level":2,"score":0.5777480602264404},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5661159753799438},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5570142865180969},{"id":"https://openalex.org/C36951298","wikidata":"https://www.wikidata.org/wiki/Q379784","display_name":"Arousal","level":2,"score":0.547730565071106},{"id":"https://openalex.org/C124805900","wikidata":"https://www.wikidata.org/wiki/Q5159269","display_name":"Conditional mutual information","level":3,"score":0.5141680240631104},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.46397098898887634},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.4586044251918793},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4528827965259552},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4457618296146393},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.4380190372467041},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3321239948272705},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.24768859148025513},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","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},{"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/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/taffc.2019.2901673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2019.2901673","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"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 Affective Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W273937395","https://openalex.org/W1239497932","https://openalex.org/W1580817707","https://openalex.org/W1588233835","https://openalex.org/W1653130573","https://openalex.org/W1964042173","https://openalex.org/W1980579221","https://openalex.org/W1985541164","https://openalex.org/W1989148514","https://openalex.org/W2002055708","https://openalex.org/W2019771222","https://openalex.org/W2032339756","https://openalex.org/W2034322657","https://openalex.org/W2039059276","https://openalex.org/W2042124323","https://openalex.org/W2042439767","https://openalex.org/W2049276185","https://openalex.org/W2064149108","https://openalex.org/W2067583143","https://openalex.org/W2081420711","https://openalex.org/W2100147270","https://openalex.org/W2104933073","https://openalex.org/W2118543857","https://openalex.org/W2120339204","https://openalex.org/W2120945046","https://openalex.org/W2128396630","https://openalex.org/W2130221071","https://openalex.org/W2133541693","https://openalex.org/W2134050473","https://openalex.org/W2134602648","https://openalex.org/W2136466671","https://openalex.org/W2144151128","https://openalex.org/W2148154194","https://openalex.org/W2155344811","https://openalex.org/W2156504490","https://openalex.org/W2160429488","https://openalex.org/W2164368909","https://openalex.org/W2170883741","https://openalex.org/W2171801645","https://openalex.org/W2184481998","https://openalex.org/W2293081071","https://openalex.org/W2528708407","https://openalex.org/W2538039704","https://openalex.org/W2547616654","https://openalex.org/W2731964405","https://openalex.org/W2775296923","https://openalex.org/W2791179640","https://openalex.org/W2953127026","https://openalex.org/W2997674406","https://openalex.org/W4210849719","https://openalex.org/W4250970868","https://openalex.org/W6675634716","https://openalex.org/W6679967756","https://openalex.org/W6682496738","https://openalex.org/W6682686508","https://openalex.org/W6683024897"],"related_works":["https://openalex.org/W4205619203","https://openalex.org/W4313429060","https://openalex.org/W3135541457","https://openalex.org/W3164528651","https://openalex.org/W181490901","https://openalex.org/W2337819340","https://openalex.org/W2044289181","https://openalex.org/W1549141376","https://openalex.org/W3048654224","https://openalex.org/W3126677997"],"abstract_inverted_index":{"Electrodermal":[0],"activity":[1],"(EDA)":[2],"is":[3],"indicative":[4],"of":[5,37,79,114],"psychological":[6],"processes":[7],"related":[8,151,187],"to":[9,118,152],"human":[10],"cognition":[11],"and":[12,41,56,65,97,103,127,146,171],"emotions.":[13],"Previous":[14],"research":[15],"has":[16,30],"studied":[17],"many":[18],"methods":[19],"for":[20,27,123,143,160,164],"extracting":[21],"EDA":[22,60,81,169],"features;":[23],"however,":[24],"their":[25],"appropriateness":[26],"emotion":[28,166],"recognition":[29,126,167],"been":[31],"tested":[32],"using":[33,83],"a":[34,76],"small":[35],"number":[36],"distinct":[38],"feature":[39,85,176],"sets":[40],"on":[42,68],"different,":[43],"usually":[44],"small,":[45],"data":[46],"sets.":[47],"In":[48],"the":[49,69,111,120,124,128,132,140,153,161,165,179],"current":[50],"research,":[51],"we":[52],"reviewed":[53],"25":[54],"studies":[55],"implemented":[57],"40":[58],"different":[59],"features":[61,82,115,150],"across":[62],"time,":[63],"frequency":[64],"time-frequency":[66],"domains":[67],"publicly":[70],"available":[71],"AMIGOS":[72],"dataset.":[73],"We":[74,107],"performed":[75],"systematic":[77],"comparison":[78],"these":[80],"three":[84],"selection":[86],"methods,":[87],"Joint":[88],"Mutual":[89,93],"Information":[90,94],"(JMI),":[91],"Conditional":[92],"Maximization":[95],"(CMIM)":[96],"Double":[98],"Input":[99],"Symmetrical":[100],"Relevance":[101],"(DISR)":[102],"machine":[104],"learning":[105],"techniques.":[106],"found":[108],"that":[109],"approximately":[110],"same":[112],"numbers":[113],"are":[116],"required":[117],"obtain":[119],"optimal":[121],"accuracy":[122],"arousal":[125,145],"valence":[129,147],"recognition.":[130,148],"Also,":[131],"subject-dependent":[133],"classification":[134,142],"results":[135],"were":[136,158],"significantly":[137],"higher":[138],"than":[139],"subject-independent":[141],"both":[144],"Statistical":[149],"Mel-Frequency":[154],"Cepstral":[155],"Coefficients":[156],"(MFCC)":[157],"explored":[159],"first":[162],"time":[163],"from":[168],"signals":[170],"they":[172],"outperformed":[173],"all":[174],"other":[175],"groups,":[177],"including":[178],"most":[180],"commonly":[181],"used":[182],"Skin":[183],"Conductance":[184],"Response":[185],"(SCR)":[186],"features.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":28},{"year":2024,"cited_by_count":54},{"year":2023,"cited_by_count":55},{"year":2022,"cited_by_count":44},{"year":2021,"cited_by_count":25},{"year":2020,"cited_by_count":20}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}