{"id":"https://openalex.org/W2745346281","doi":"https://doi.org/10.1109/acii.2017.8273639","title":"DeepBreath: Deep learning of breathing patterns for automatic stress recognition using low-cost thermal imaging in unconstrained settings","display_name":"DeepBreath: Deep learning of breathing patterns for automatic stress recognition using low-cost thermal imaging in unconstrained settings","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2745346281","doi":"https://doi.org/10.1109/acii.2017.8273639","mag":"2745346281"},"language":"en","primary_location":{"id":"doi:10.1109/acii.2017.8273639","doi":"https://doi.org/10.1109/acii.2017.8273639","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acii.2017.8273639","pdf_url":null,"source":{"id":"https://openalex.org/S4393918207","display_name":"International Conference on Affective Computing and Intelligent Interaction and workshops","issn_l":"2156-8103","issn":["2156-8103"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1"],"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":"2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1708.06026","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069669556","display_name":"Youngjun Cho","orcid":"https://orcid.org/0000-0001-5695-0759","observed_orcids":["https://orcid.org/0000-0001-5695-0759"]},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Youngjun Cho","raw_affiliation_strings":["Faculty of Brain Sciences, UCL Interaction Centre, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Brain Sciences, UCL Interaction Centre, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072897829","display_name":"Nadia Bianchi\u2010Berthouze","orcid":"https://orcid.org/0000-0001-8921-0044","observed_orcids":["https://orcid.org/0000-0001-8921-0044"]},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Nadia Bianchi-Berthouze","raw_affiliation_strings":["Faculty of Brain Sciences, UCL Interaction Centre, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Brain Sciences, UCL Interaction Centre, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049634973","display_name":"Simon Julier","orcid":"https://orcid.org/0000-0003-4380-137X","observed_orcids":["https://orcid.org/0000-0003-4380-137X"]},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Simon J. Julier","raw_affiliation_strings":["Department of Computer Science, University College London, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University College London, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I45129253"],"apc_list":null,"apc_paid":null,"fwci":9.1195,"has_fulltext":false,"cited_by_count":124,"citation_normalized_percentile":{"value":0.97888068,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"456","last_page":"463"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9589999914169312,"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":0.9589999914169312,"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/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.013000000268220901,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.011300000362098217,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/stress-detection","display_name":"stress detection","score":0.7730000019073486},{"id":"https://openalex.org/keywords/breathing-pattern","display_name":"breathing pattern","score":0.8920000195503235},{"id":"https://openalex.org/keywords/infrared-thermography","display_name":"infrared thermography","score":0.7710000276565552},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.7910000085830688},{"id":"https://openalex.org/keywords/mental-workload","display_name":"mental workload","score":0.6359999775886536},{"id":"https://openalex.org/keywords/cognitive-load","display_name":"cognitive load","score":0.5929999947547913},{"id":"https://openalex.org/keywords/stroop-task","display_name":"Stroop task","score":0.8090000152587891},{"id":"https://openalex.org/keywords/mental-arithmetic","display_name":"mental arithmetic","score":0.6380000114440918},{"id":"https://openalex.org/keywords/data-augmentation","display_name":"data augmentation","score":0.824999988079071},{"id":"https://openalex.org/keywords/low-cost-sensors","display_name":"low-cost sensors","score":0.4699999988079071}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7555999755859375},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7421000003814697},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.7342000007629395},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7195000052452087},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6417999863624573},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5921000242233276},{"id":"https://openalex.org/C39300077","wikidata":"https://www.wikidata.org/wiki/Q9530","display_name":"Breathing","level":2,"score":0.5591999888420105},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4399999976158142},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4106999933719635},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3686999976634979},{"id":"https://openalex.org/C21036866","wikidata":"https://www.wikidata.org/wiki/Q181767","display_name":"Stress (linguistics)","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.26809999346733093},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2628999948501587}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/acii.2017.8273639","doi":"https://doi.org/10.1109/acii.2017.8273639","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acii.2017.8273639","pdf_url":null,"source":{"id":"https://openalex.org/S4393918207","display_name":"International Conference on Affective Computing and Intelligent Interaction and workshops","issn_l":"2156-8103","issn":["2156-8103"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1"],"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":"2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1708.06026","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.06026","pdf_url":"https://arxiv.org/pdf/1708.06026","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"doi:10.48550/arxiv.1708.06026","doi":"https://doi.org/10.48550/arxiv.1708.06026","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1708.06026","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1708.06026","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.06026","pdf_url":"https://arxiv.org/pdf/1708.06026","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.5683000087738037,"display_name":"Good health and well-being"}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1538131130","https://openalex.org/W1974210421","https://openalex.org/W1974925866","https://openalex.org/W1984167894","https://openalex.org/W1989652160","https://openalex.org/W1994262406","https://openalex.org/W1997430507","https://openalex.org/W1997769138","https://openalex.org/W2006767569","https://openalex.org/W2024221294","https://openalex.org/W2039507996","https://openalex.org/W2071256705","https://openalex.org/W2081189996","https://openalex.org/W2085904945","https://openalex.org/W2097117768","https://openalex.org/W2098335992","https://openalex.org/W2105036571","https://openalex.org/W2105943885","https://openalex.org/W2111166412","https://openalex.org/W2120357670","https://openalex.org/W2127547994","https://openalex.org/W2132148016","https://openalex.org/W2144101679","https://openalex.org/W2144279833","https://openalex.org/W2146558719","https://openalex.org/W2162630407","https://openalex.org/W2163605009","https://openalex.org/W2171801645","https://openalex.org/W2173931240","https://openalex.org/W2184409518","https://openalex.org/W2246249023","https://openalex.org/W2328363150","https://openalex.org/W2394865193","https://openalex.org/W2399733683","https://openalex.org/W2755547982","https://openalex.org/W2919115771"],"related_works":["https://openalex.org/W4313525327","https://openalex.org/W2404267262","https://openalex.org/W4413278309","https://openalex.org/W7045514568","https://openalex.org/W6996873599","https://openalex.org/W7147673801","https://openalex.org/W2787695726","https://openalex.org/W4205515185","https://openalex.org/W7166192106","https://openalex.org/W2624958217"],"abstract_inverted_index":{"We":[0],"propose":[1],"DeepBreath,":[2],"a":[3,21,28,84,90,110,132,141,211],"deep":[4,91,121],"learning":[5,207],"model":[6,145],"which":[7],"automatically":[8],"recognises":[9],"people's":[10],"psychological":[11],"stress":[12,192],"level":[13],"(mental":[14],"overload)":[15],"from":[16,115,135,153],"their":[17],"breathing":[18,30,57,63,81],"patterns.":[19],"Using":[20,175],"low":[22],"cost":[23],"thermal":[24,221],"camera,":[25],"we":[26,59],"track":[27],"person's":[29],"patterns":[31],"as":[32,178],"temperature":[33],"changes":[34],"around":[35],"his/her":[36],"nostril.":[37],"The":[38,73,144],"paper's":[39],"technical":[40],"contribution":[41],"is":[42,96,123,146],"threefold.":[43],"First":[44],"of":[45,48,55,79,106,159,171,191,219],"all,":[46],"instead":[47],"creating":[49],"handcrafted":[50],"features":[51],"to":[52,99,125,129,140,156,226],"capture":[53,76],"aspects":[54],"the":[56,61,77,80,100,104,127,181,202,217,227],"patterns,":[58],"transform":[60],"uni-dimensional":[62],"signals":[64],"into":[65],"two":[66,157,189],"dimensional":[67],"respiration":[68],"variability":[69],"spectrogram":[70,101],"(RVS)":[71],"sequences.":[72],"spectrograms":[74],"easily":[75],"complexity":[78],"dynamics.":[82],"Second,":[83],"spatial":[85],"pattern":[86],"analysis":[87],"based":[88,209],"on":[89,210],"Convolutional":[92],"Neural":[93],"Network":[94],"(CNN)":[95],"directly":[97],"applied":[98,124],"sequences":[102],"without":[103],"need":[105],"hand-crafting":[107],"features.":[108],"Finally,":[109,216],"data":[111,151],"augmentation":[112],"technique,":[113],"inspired":[114],"solutions":[116],"for":[117],"over-fitting":[118],"problems":[119],"in":[120,186,195],"learning,":[122],"allow":[126],"CNN":[128,182,203],"learn":[130],"with":[131,150,169],"small-scale":[133],"dataset":[134,218],"short-term":[136],"measurements":[137],"(e.g.,":[138],"up":[139],"few":[142],"hours).":[143],"trained":[147],"and":[148,193],"tested":[149],"collected":[152],"people":[154],"exposed":[155],"types":[158],"cognitive":[160],"tasks":[161],"(Stroop":[162],"Colour":[163],"Word":[164],"Test,":[165],"Mental":[166],"Computation":[167],"test)":[168],"sessions":[170],"different":[172],"difficulty":[173],"levels.":[174,199],"normalised":[176],"self-report":[177],"ground":[179],"truth,":[180],"reaches":[183],"84.59%":[184],"accuracy":[185],"discriminating":[187,196],"between":[188,197],"levels":[190],"56.52%":[194],"three":[198],"In":[200],"addition,":[201],"outperformed":[204],"powerful":[205],"shallow":[206],"methods":[208],"single":[212],"layer":[213],"neural":[214],"network.":[215],"labelled":[220],"images":[222],"will":[223],"be":[224],"open":[225],"community.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1}],"updated_date":"2026-10-27T15:51:10.671819","created_date":"2017-08-31T00:00:00"}