{"id":"https://openalex.org/W2187334453","doi":"https://doi.org/10.1109/idaacs.2015.7340738","title":"Pain detection from facial characteristics using supervised descent method","display_name":"Pain detection from facial characteristics using supervised descent method","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2187334453","doi":"https://doi.org/10.1109/idaacs.2015.7340738","mag":"2187334453"},"language":"en","primary_location":{"id":"doi:10.1109/idaacs.2015.7340738","doi":"https://doi.org/10.1109/idaacs.2015.7340738","is_oa":false,"landing_page_url":"https://doi.org/10.1109/idaacs.2015.7340738","pdf_url":null,"source":{"id":"https://openalex.org/S4363607971","display_name":"IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","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":"2015 IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5024572246","display_name":"Nikolay N. Neshov","orcid":"https://orcid.org/0000-0002-9657-4847","observed_orcids":["https://orcid.org/0000-0002-9657-4847"]},"institutions":[{"id":"https://openalex.org/I31151848","display_name":"Technical University of Sofia","ror":"https://ror.org/052prhs50","country_code":"BG","type":"education","lineage":["https://openalex.org/I31151848"]}],"countries":["BG"],"is_corresponding":false,"raw_author_name":"Nikolay Neshov","raw_affiliation_strings":["Technical University of Sofia, Sofia, Bulgaria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Sofia, Sofia, Bulgaria","institution_ids":["https://openalex.org/I31151848"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054696693","display_name":"Agata H. Manolova","orcid":"https://orcid.org/0000-0002-8120-363X","observed_orcids":["https://orcid.org/0000-0002-8120-363X"]},"institutions":[{"id":"https://openalex.org/I31151848","display_name":"Technical University of Sofia","ror":"https://ror.org/052prhs50","country_code":"BG","type":"education","lineage":["https://openalex.org/I31151848"]}],"countries":["BG"],"is_corresponding":false,"raw_author_name":"Agata Manolova","raw_affiliation_strings":["Technical University of Sofia, Sofia, Bulgaria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Sofia, Sofia, Bulgaria","institution_ids":["https://openalex.org/I31151848"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I31151848"],"apc_list":null,"apc_paid":null,"fwci":1.6111,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.86452682,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"251","last_page":"256"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.5590999722480774,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.5590999722480774,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.37209999561309814,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.013299999758601189,"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/pain-detection","display_name":"pain detection","score":0.8090000152587891},{"id":"https://openalex.org/keywords/facial-expression-analysis","display_name":"facial expression analysis","score":0.972000002861023},{"id":"https://openalex.org/keywords/supervised-descent-method","display_name":"supervised descent method","score":0.7770000100135803},{"id":"https://openalex.org/keywords/pain-intensity-estimation","display_name":"pain intensity estimation","score":0.7630000114440918},{"id":"https://openalex.org/keywords/facial-landmark-detection","display_name":"facial landmark detection","score":0.6259999871253967},{"id":"https://openalex.org/keywords/sift-features","display_name":"SIFT features","score":0.7549999952316284},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.9359999895095825},{"id":"https://openalex.org/keywords/linear-regression","display_name":"linear regression","score":0.8479999899864197},{"id":"https://openalex.org/keywords/shoulder-pain","display_name":"shoulder pain","score":0.8870000243186951},{"id":"https://openalex.org/keywords/remote-patient-monitoring","display_name":"remote patient monitoring","score":0.5839999914169312}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6555537581443787},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.6105958819389343},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5743042826652527},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5449160933494568},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.46590763330459595},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4301459491252899},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.41889190673828125},{"id":"https://openalex.org/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"score":0.39009392261505127},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37875255942344666},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32032549381256104},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2690490782260895},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.137993723154068},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1214895248413086},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/idaacs.2015.7340738","doi":"https://doi.org/10.1109/idaacs.2015.7340738","is_oa":false,"landing_page_url":"https://doi.org/10.1109/idaacs.2015.7340738","pdf_url":null,"source":{"id":"https://openalex.org/S4363607971","display_name":"IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","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":"2015 IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.8199999928474426}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W260234364","https://openalex.org/W1590099432","https://openalex.org/W1772325009","https://openalex.org/W2020311932","https://openalex.org/W2049640633","https://openalex.org/W2077847255","https://openalex.org/W2090495691","https://openalex.org/W2098615198","https://openalex.org/W2101545465","https://openalex.org/W2106043670","https://openalex.org/W2112085218","https://openalex.org/W2125208830","https://openalex.org/W2126437449","https://openalex.org/W2137843194","https://openalex.org/W2151103935","https://openalex.org/W2153635508","https://openalex.org/W2157285372","https://openalex.org/W2159668072","https://openalex.org/W2164598857","https://openalex.org/W2166087694","https://openalex.org/W3120421331"],"related_works":["https://openalex.org/W6968309670","https://openalex.org/W2330996833","https://openalex.org/W2098615198","https://openalex.org/W7097857869","https://openalex.org/W2973170939","https://openalex.org/W2072439449","https://openalex.org/W1978963692","https://openalex.org/W2888089332","https://openalex.org/W4295916826","https://openalex.org/W4210336963"],"abstract_inverted_index":{"Current":[0],"methods":[1],"of":[2,17,54,112,220,225],"assessing":[3],"pain":[4,41,55,72,106,125,129,135,185,199,210],"depend":[5],"almost":[6],"entirely":[7],"on":[8,139,176,236],"verbal":[9,69],"report":[10,70],"such":[11],"as":[12],"clinical":[13],"interview":[14],"or":[15,82,94],"questionnaires":[16],"the":[18,36,52,56,90,148,168,183,209],"patients.":[19],"Pain":[20],"being":[21],"a":[22,32,63,101,173,237],"symptom":[23],"that":[24,232],"can":[25],"neither":[26],"be":[27],"felt":[28],"nor":[29],"seen,":[30],"poses":[31],"major":[33],"problem":[34],"for":[35,122,182],"medical":[37,66,102],"personnel":[38],"involved":[39],"in":[40,107,131,147],"management":[42],"since":[43],"there":[44],"are":[45],"no":[46],"accurate":[47],"objective":[48],"measures":[49],"to":[50,80,87],"establish":[51],"extent":[53],"patient":[57],"is":[58,111],"suffering":[59],"from":[60],"when":[61,77],"using":[62,161],"remote":[64],"assistive":[65,103],"system.":[67],"The":[68,193,227],"grading":[71],"has":[73],"obvious":[74],"discrepancies,":[75],"especially":[76],"it":[78],"comes":[79],"children":[81],"people":[83],"with":[84,195,197],"limited":[85],"ability":[86],"communicate":[88],"(i.e.":[89,127],"mute,":[91],"mentally":[92],"impaired,":[93],"patients":[95,196],"having":[96],"assisted":[97],"breathing).":[98],"When":[99],"designing":[100],"system":[104],"measuring":[105],"an":[108,120,215],"efficient":[109],"way":[110],"great":[113],"importance.":[114],"In":[115],"this":[116],"paper":[117],"we":[118,150,171,189,213],"proposes":[119],"algorithm":[121],"both":[123],"automatic":[124],"recognition":[126,169,203],"pain/no":[128],"presence":[130],"human)":[132],"and":[133,156,181,222],"continuous":[134,184],"intensity":[136,186,211],"estimation":[137,187,212],"based":[138,175],"facial":[140],"expression":[141],"analysis.":[142],"To":[143],"locate":[144],"specific":[145],"landmarks":[146],"face":[149],"used":[151],"Supervised":[152],"Descent":[153],"Method":[154],"(SDM)":[155],"then":[157],"extract":[158],"feature":[159],"vectors":[160],"Scale":[162],"Invariant":[163],"Feature":[164],"Transform":[165],"(SIFT).":[166],"For":[167,208],"task":[170,188],"build":[172],"classier":[174],"Support":[177],"Vector":[178],"Machines":[179],"(SVM)":[180],"trained":[190],"linear":[191],"regressor.":[192],"experiments":[194],"shoulder":[198],"show":[200],"very":[201],"good":[202],"rate":[204],"(more":[205],"than":[206],"95.7%).":[207],"reached":[214],"average":[216],"Mean":[217],"Squared":[218],"Error":[219],"1.28":[221],"Correlation":[223],"coefficient":[224],"0.59.":[226],"recorded":[228],"results":[229,235],"demonstrate":[230],"performance":[231],"exceeds":[233],"state-of-the-art":[234],"standard":[238],"data":[239],"set.":[240]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2016-06-24T00:00:00"}
