{"id":"https://openalex.org/W2019771222","doi":"https://doi.org/10.1109/tsmca.2012.2210408","title":"Emotional State Classification in Patient\u2013Robot Interaction Using Wavelet Analysis and Statistics-Based Feature Selection","display_name":"Emotional State Classification in Patient\u2013Robot Interaction Using Wavelet Analysis and Statistics-Based Feature Selection","publication_year":2012,"publication_date":"2012-09-12","ids":{"openalex":"https://openalex.org/W2019771222","doi":"https://doi.org/10.1109/tsmca.2012.2210408","mag":"2019771222"},"language":"en","primary_location":{"id":"doi:10.1109/tsmca.2012.2210408","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmca.2012.2210408","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"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 Human-Machine Systems","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/A5113577924","display_name":"Manida Swangnetr","orcid":null},"institutions":[{"id":"https://openalex.org/I179193067","display_name":"Khon Kaen University","ror":"https://ror.org/03cq4gr50","country_code":"TH","type":"education","lineage":["https://openalex.org/I179193067"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Manida Swangnetr","raw_affiliation_strings":["Back, Neck, and Other Join Pain Research Group, Department of Production Technology, Khon Kaen University, Khon Kaen, Thailand","Dept. of Production Technol., Khon Kaen Univ., Khon Kaen, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Back, Neck, and Other Join Pain Research Group, Department of Production Technology, Khon Kaen University, Khon Kaen, Thailand","institution_ids":["https://openalex.org/I179193067"]},{"raw_affiliation_string":"Dept. of Production Technol., Khon Kaen Univ., Khon Kaen, Thailand","institution_ids":["https://openalex.org/I179193067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075585171","display_name":"David Kaber","orcid":"https://orcid.org/0000-0003-3413-1503"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David B. Kaber","raw_affiliation_strings":["Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, NC, USA","Edward P. Fitts Dept. of Ind. & Syst. Eng., North Carolina State Univ., Raleigh, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]},{"raw_affiliation_string":"Edward P. Fitts Dept. of Ind. & Syst. Eng., North Carolina State Univ., Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.9461,"has_fulltext":false,"cited_by_count":112,"citation_normalized_percentile":{"value":0.95920923,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"43","issue":"1","first_page":"63","last_page":"75"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9979000091552734,"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":0.9979000091552734,"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":0.9976999759674072,"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":0.9976999759674072,"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/wavelet","display_name":"Wavelet","score":0.6641883850097656},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6115772724151611},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5539721250534058},{"id":"https://openalex.org/keywords/valence","display_name":"Valence (chemistry)","score":0.5418016314506531},{"id":"https://openalex.org/keywords/arousal","display_name":"Arousal","score":0.5401334762573242},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5390206575393677},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5219885110855103},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49854326248168945},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47336408495903015},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4299103319644928},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3641274571418762},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.34446239471435547},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32616013288497925},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.14805173873901367}],"concepts":[{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6641883850097656},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6115772724151611},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5539721250534058},{"id":"https://openalex.org/C168900304","wikidata":"https://www.wikidata.org/wiki/Q171407","display_name":"Valence (chemistry)","level":2,"score":0.5418016314506531},{"id":"https://openalex.org/C36951298","wikidata":"https://www.wikidata.org/wiki/Q379784","display_name":"Arousal","level":2,"score":0.5401334762573242},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5390206575393677},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5219885110855103},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49854326248168945},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47336408495903015},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4299103319644928},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3641274571418762},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34446239471435547},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32616013288497925},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.14805173873901367},{"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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/tsmca.2012.2210408","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmca.2012.2210408","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"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 Human-Machine Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309637","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W231870665","https://openalex.org/W1515990995","https://openalex.org/W1533318183","https://openalex.org/W1533618852","https://openalex.org/W1584471057","https://openalex.org/W1596960200","https://openalex.org/W1602360832","https://openalex.org/W1821352908","https://openalex.org/W1941711934","https://openalex.org/W1963691065","https://openalex.org/W1964751118","https://openalex.org/W1966797434","https://openalex.org/W1981219199","https://openalex.org/W1981799567","https://openalex.org/W1989104072","https://openalex.org/W1989976960","https://openalex.org/W1997494785","https://openalex.org/W2007098914","https://openalex.org/W2007461783","https://openalex.org/W2012271905","https://openalex.org/W2037146600","https://openalex.org/W2053029502","https://openalex.org/W2064149108","https://openalex.org/W2073779083","https://openalex.org/W2080126518","https://openalex.org/W2080795763","https://openalex.org/W2084397606","https://openalex.org/W2092804630","https://openalex.org/W2097340087","https://openalex.org/W2104126273","https://openalex.org/W2105923830","https://openalex.org/W2111438996","https://openalex.org/W2126292754","https://openalex.org/W2132311854","https://openalex.org/W2133589238","https://openalex.org/W2137647199","https://openalex.org/W2143969506","https://openalex.org/W2144855015","https://openalex.org/W2145710484","https://openalex.org/W2149628368","https://openalex.org/W2157019309","https://openalex.org/W2167557160","https://openalex.org/W2505415825","https://openalex.org/W2994886742","https://openalex.org/W4294877277","https://openalex.org/W6683192370"],"related_works":["https://openalex.org/W2029072726","https://openalex.org/W91913183","https://openalex.org/W2936882366","https://openalex.org/W1987182177","https://openalex.org/W2736893848","https://openalex.org/W2128698257","https://openalex.org/W1544055438","https://openalex.org/W3003450285","https://openalex.org/W2085024878","https://openalex.org/W4361008003"],"abstract_inverted_index":{"Due":[0],"to":[1,16,31,38,42,47,59,132,212,257],"a":[2,29,61,91,146,182],"major":[3],"shortage":[4],"of":[5,55,113,149,173,198,208,218,221,250],"nurses":[6],"in":[7,19,51,71,215],"the":[8,36,199,216,228],"U.S.,":[9],"future":[10,245],"healthcare":[11,260],"service":[12,246],"robots":[13,34,75],"are":[14],"expected":[15],"be":[17],"used":[18,180],"tasks":[20],"involving":[21],"direct":[22],"interaction":[23,72],"with":[24,35,73,93],"patients.":[25],"Consequently,":[26],"there":[27],"is":[28],"need":[30],"design":[32],"nursing":[33,74,88],"capability":[37],"detect":[39],"and":[40,46,103,116,144,162,164,190,202,224,231,233,254],"respond":[41],"patient":[43,67,251],"emotional":[44,68,126,150,186,222,252],"states":[45,223,253],"facilitate":[48],"positive":[49,259],"experiences":[50],"healthcare.":[52],"The":[53,235],"objective":[54],"this":[56],"study":[57],"was":[58,84,130,156,179],"develop":[60],"new":[62,236],"computational":[63],"algorithm":[64,129,237],"for":[65,184,244],"accurate":[66],"state":[69,127,187],"classification":[70,128],"during":[76],"medical":[77],"service.":[78],"A":[79,124,152,171],"simulated":[80],"medicine":[81],"delivery":[82],"experiment":[83],"conducted":[85],"at":[86],"two":[87],"homes":[89],"using":[90,168],"robot":[92,247],"different":[94],"human-like":[95],"features.":[96,205],"Physiological":[97],"signals,":[98],"including":[99],"heart":[100],"rate":[101],"(HR)":[102],"galvanic":[104],"skin":[105],"response":[106,230],"(GSR),":[107],"as":[108,110,181,240],"well":[109],"subjective":[111],"ratings":[112],"valence":[114,191],"(happy-unhappy)":[115],"arousal":[117,232],"(excited-bored)":[118],"were":[119,160,165,192],"collected":[120],"on":[121],"elderly":[122],"residents.":[123],"three-stage":[125],"applied":[131],"these":[133],"data,":[134],"including:":[135],"(1)":[136],"physiological":[137,229],"feature":[138,142],"extraction;":[139],"(2)":[140],"statistical-based":[141],"selection;":[143],"(3)":[145],"machine-learning":[147],"model":[148],"states.":[151],"pre-processed":[153],"HR":[154,200],"signal":[155,201],"used.":[157],"GSR":[158,177,203,209],"signals":[159,210],"nonstationary":[161],"noisy":[163],"further":[166],"processed":[167],"wavelet":[169,174,204],"analysis.":[170],"set":[172],"coefficients,":[175],"representing":[176],"features,":[178],"basis":[183],"current":[185],"classification.":[188],"Arousal":[189],"significantly":[193],"explained":[194],"by":[195],"statistical":[196],"features":[197],"Wavelet-based":[206],"de-noising":[207],"led":[211],"an":[213,241],"increase":[214],"percentage":[217],"correct":[219],"classifications":[220],"clearer":[225],"relationships":[226],"among":[227],"valence.":[234],"may":[238],"serve":[239],"effective":[242],"method":[243],"real-time":[248],"detection":[249],"behavior":[255],"adaptation":[256],"promote":[258],"experiences.":[261]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":14},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":9},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
