{"id":"https://openalex.org/W3021025455","doi":"https://doi.org/10.1109/ciss48834.2020.1570617362","title":"Deep Learning based Affective Sensing with Remote Photoplethysmography","display_name":"Deep Learning based Affective Sensing with Remote Photoplethysmography","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3021025455","doi":"https://doi.org/10.1109/ciss48834.2020.1570617362","mag":"3021025455"},"language":"en","primary_location":{"id":"doi:10.1109/ciss48834.2020.1570617362","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss48834.2020.1570617362","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 54th Annual Conference on Information Sciences and Systems (CISS)","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/A5043602487","display_name":"T. S. Luguev","orcid":"https://orcid.org/0000-0002-2294-9298"},"institutions":[{"id":"https://openalex.org/I4210124274","display_name":"Fraunhofer Institute for Integrated Circuits","ror":"https://ror.org/024ape423","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210124274","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Timur Luguev","raw_affiliation_strings":["Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany","institution_ids":["https://openalex.org/I4210124274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108710241","display_name":"Dominik Seus","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124274","display_name":"Fraunhofer Institute for Integrated Circuits","ror":"https://ror.org/024ape423","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210124274","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dominik Seus","raw_affiliation_strings":["Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany","institution_ids":["https://openalex.org/I4210124274"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061812704","display_name":"Jens-Uwe Garbas","orcid":"https://orcid.org/0000-0003-3473-0370"},"institutions":[{"id":"https://openalex.org/I4210124274","display_name":"Fraunhofer Institute for Integrated Circuits","ror":"https://ror.org/024ape423","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210124274","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jens-Uwe Garbas","raw_affiliation_strings":["Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany","institution_ids":["https://openalex.org/I4210124274"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043602487"],"corresponding_institution_ids":["https://openalex.org/I4210124274"],"apc_list":null,"apc_paid":null,"fwci":0.7725,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.67607021,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9939000010490417,"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/photoplethysmogram","display_name":"Photoplethysmogram","score":0.8716440200805664},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7321407794952393},{"id":"https://openalex.org/keywords/heart-rate-variability","display_name":"Heart rate variability","score":0.7311474084854126},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6564980745315552},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5534642934799194},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4801044762134552},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.45638707280158997},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.42564231157302856},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.41941431164741516},{"id":"https://openalex.org/keywords/affective-computing","display_name":"Affective computing","score":0.4193372130393982},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.4147946834564209},{"id":"https://openalex.org/keywords/heart-rate","display_name":"Heart rate","score":0.1667792797088623},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10118690133094788},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.072197824716568}],"concepts":[{"id":"https://openalex.org/C116390426","wikidata":"https://www.wikidata.org/wiki/Q7187885","display_name":"Photoplethysmogram","level":3,"score":0.8716440200805664},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7321407794952393},{"id":"https://openalex.org/C71635504","wikidata":"https://www.wikidata.org/wiki/Q933954","display_name":"Heart rate variability","level":4,"score":0.7311474084854126},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6564980745315552},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5534642934799194},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4801044762134552},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.45638707280158997},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.42564231157302856},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.41941431164741516},{"id":"https://openalex.org/C6438553","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Affective computing","level":2,"score":0.4193372130393982},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.4147946834564209},{"id":"https://openalex.org/C2777953023","wikidata":"https://www.wikidata.org/wiki/Q1073121","display_name":"Heart rate","level":3,"score":0.1667792797088623},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10118690133094788},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.072197824716568},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"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/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ciss48834.2020.1570617362","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss48834.2020.1570617362","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 54th Annual Conference on Information Sciences and Systems (CISS)","raw_type":"proceedings-article"},{"id":"pmh:oai:fraunhofer.de:N-596007","is_oa":false,"landing_page_url":"http://publica.fraunhofer.de/documents/N-596007.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IIS","raw_type":"Conference Paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/408577","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/408577","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2008821584","https://openalex.org/W2026588572","https://openalex.org/W2122098299","https://openalex.org/W2313602734","https://openalex.org/W2534209845","https://openalex.org/W2585933352","https://openalex.org/W2726034082","https://openalex.org/W2787182113","https://openalex.org/W2801411683","https://openalex.org/W2804850800","https://openalex.org/W2893517024","https://openalex.org/W2898850655","https://openalex.org/W2903521046","https://openalex.org/W2963433879","https://openalex.org/W2980584869","https://openalex.org/W6754458465"],"related_works":["https://openalex.org/W3196000489","https://openalex.org/W2092419518","https://openalex.org/W1489924780","https://openalex.org/W2135573418","https://openalex.org/W2773864994","https://openalex.org/W2745497104","https://openalex.org/W1997400788","https://openalex.org/W2775620487","https://openalex.org/W2112393832","https://openalex.org/W2722112567"],"abstract_inverted_index":{"Recent":[0],"studies":[1,46],"show":[2],"that":[3,13,120],"heart":[4,54],"rate":[5,55],"variability":[6],"(HRV)":[7],"is":[8,75,86],"an":[9],"important":[10],"physiological":[11,15,126],"characteristic":[12],"reflects":[14],"and":[16,82],"affective":[17,79,152],"states":[18],"of":[19,26,34,44,47,62,67,84,132],"a":[20,90],"person.":[21],"Advancements":[22],"in":[23,151],"the":[24,39,72,130],"field":[25],"remote":[27,63,148],"camera-based":[28,48],"photoplethysmography":[29],"has":[30],"made":[31],"possible":[32],"measurement":[33,83],"cardiac":[35],"signals":[36],"using":[37],"just":[38,53],"raw":[40,103],"face":[41,122],"videos.":[42,105],"Most":[43],"existing":[45],"cardiovascular":[49],"monitoring":[50],"focus":[51],"on":[52,116],"(HR)":[56],"estimation,":[57],"leaving":[58],"more":[59],"interesting":[60],"case":[61],"HRV":[64,85,100,139,149],"estimation":[65,150],"out":[66],"scope.":[68],"However,":[69],"knowing":[70],"only":[71],"average":[73],"HR":[74],"not":[76],"enough":[77],"for":[78,98,138,146],"sensing":[80,153],"applications,":[81],"beneficial.":[87],"We":[88,141],"propose":[89],"new":[91],"framework,":[92],"which":[93],"uses":[94],"deep":[95,134],"spatiotemporal":[96],"networks":[97],"contactless":[99],"measurements":[101],"from":[102],"facial":[104],"The":[106],"proposed":[107],"framework":[108],"employs":[109],"data":[110],"augmentation":[111],"technique.":[112],"It":[113],"was":[114],"evaluated":[115],"two":[117],"multimodal":[118],"databases":[119],"consists":[121],"videos":[123],"with":[124],"synchronized":[125],"signals.":[127],"Experiments":[128],"demonstrate":[129],"advantage":[131],"our":[133],"learning":[135],"based":[136],"approach":[137],"estimation.":[140],"also":[142],"achieved":[143],"promising":[144],"results":[145],"inclusion":[147],"applications.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
