{"id":"https://openalex.org/W2129807774","doi":"https://doi.org/10.1109/waci.2011.5953149","title":"Extracting coherent emotion elicited segments from physiological signals","display_name":"Extracting coherent emotion elicited segments from physiological signals","publication_year":2011,"publication_date":"2011-04-01","ids":{"openalex":"https://openalex.org/W2129807774","doi":"https://doi.org/10.1109/waci.2011.5953149","mag":"2129807774"},"language":"en","primary_location":{"id":"doi:10.1109/waci.2011.5953149","is_oa":false,"landing_page_url":"https://doi.org/10.1109/waci.2011.5953149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Workshop on Affective Computational Intelligence (WACI)","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/A5032946317","display_name":"Chi-Keng Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chi-Keng Wu","raw_affiliation_strings":["Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan","Department of Electrical Engineering, National Cheng Kung University, Tainan (Taiwan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]},{"raw_affiliation_string":"Department of Electrical Engineering, National Cheng Kung University, Tainan (Taiwan)","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048480773","display_name":"Pau\u2010Choo Chung","orcid":"https://orcid.org/0000-0002-8660-570X"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Pau-Choo Chung","raw_affiliation_strings":["Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan","Department of Electrical Engineering, National Cheng Kung University, Tainan (Taiwan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]},{"raw_affiliation_string":"Department of Electrical Engineering, National Cheng Kung University, Tainan (Taiwan)","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"last","author":{"id":null,"display_name":"Chi-Jen Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chi-Jen Wang","raw_affiliation_strings":["Department of Nursing, National Cheng Kung University, Tainan, Taiwan","Dept. of Nursing, Nat. Cheng Kung Univ., Tainan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Nursing, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]},{"raw_affiliation_string":"Dept. of Nursing, Nat. Cheng Kung Univ., Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1843,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.82022731,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9901000261306763,"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/T12496","display_name":"Color perception and design","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bhattacharyya-distance","display_name":"Bhattacharyya distance","score":0.8542050123214722},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6911371350288391},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6656527519226074},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.655659019947052},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.6344212293624878},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6125233769416809},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.60256028175354},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.537049412727356},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5274512767791748},{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.5102083683013916},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.48496460914611816},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47641265392303467},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.46094900369644165},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4390747845172882},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4109169542789459},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32812100648880005},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22217708826065063},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1513327658176422}],"concepts":[{"id":"https://openalex.org/C24145651","wikidata":"https://www.wikidata.org/wiki/Q2901249","display_name":"Bhattacharyya distance","level":2,"score":0.8542050123214722},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6911371350288391},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6656527519226074},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.655659019947052},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.6344212293624878},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6125233769416809},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.60256028175354},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.537049412727356},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5274512767791748},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.5102083683013916},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.48496460914611816},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47641265392303467},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.46094900369644165},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4390747845172882},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4109169542789459},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32812100648880005},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22217708826065063},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1513327658176422},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/waci.2011.5953149","is_oa":false,"landing_page_url":"https://doi.org/10.1109/waci.2011.5953149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Workshop on Affective Computational Intelligence (WACI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1518433044","https://openalex.org/W1994518960","https://openalex.org/W2051224630","https://openalex.org/W2078671978","https://openalex.org/W2109294327","https://openalex.org/W2117645142","https://openalex.org/W2118769274","https://openalex.org/W2120945046","https://openalex.org/W2127429655","https://openalex.org/W2131274108","https://openalex.org/W2149197198","https://openalex.org/W2156503193","https://openalex.org/W2164368909"],"related_works":["https://openalex.org/W1982681402","https://openalex.org/W3149747767","https://openalex.org/W1536747792","https://openalex.org/W2192403599","https://openalex.org/W2366937720","https://openalex.org/W2163087802","https://openalex.org/W2155818328","https://openalex.org/W2121699558","https://openalex.org/W4244450895","https://openalex.org/W2074399518"],"abstract_inverted_index":{"The":[0],"feasibility":[1],"of":[2,89],"real":[3],"life":[4],"affective":[5],"detection":[6],"using":[7,42],"physiological":[8,56,75],"signals":[9],"is":[10,19,45,91],"usually":[11],"limited":[12],"by":[13],"biosensor":[14],"noise":[15],"and":[16,39,51,106],"artifact.":[17],"This":[18],"challenging":[20],"in":[21],"extracting":[22],"the":[23,49],"representative":[24,95],"emotion":[25,63],"features.":[26],"In":[27,77],"this":[28,78],"paper":[29,79],"a":[30,80],"quasi-homogeneous":[31],"segmentation":[32],"algorithm":[33],"based":[34,84],"on":[35,85],"Top-Down":[36],"homogeneous":[37],"splitting":[38],"Bottom-Up":[40],"Merging":[41],"Bhattacharyya":[43],"distance":[44],"proposed":[46],"to":[47,93],"partition":[48],"signal":[50],"remove":[52],"artifacts.":[53],"Furthermore,":[54],"since":[55],"responses":[57],"may":[58],"also":[59],"vary":[60],"within":[61],"one":[62],"elicited":[64],"period,":[65],"features":[66],"extracted":[67],"from":[68],"segmented":[69],"segments":[70,97],"can":[71],"better":[72],"describe":[73],"recent":[74],"patterns.":[76],"constraint-based":[81],"clustering":[82],"analysis":[83],"estimating":[86],"best":[87],"seed":[88],"K-means":[90],"developed":[92],"discover":[94],"emotion-elicited":[96],"at":[98],"all":[99],"cross":[100],"subject":[101],"partitions":[102],"which":[103],"include":[104],"labeled":[105],"unlabelled":[107],"feature":[108],"vectors.":[109]},"counts_by_year":[{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}