{"id":"https://openalex.org/W3035959578","doi":"https://doi.org/10.1109/cvprw50498.2020.00152","title":"HeartTrack: Convolutional neural network for remote video-based heart rate monitoring","display_name":"HeartTrack: Convolutional neural network for remote video-based heart rate monitoring","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3035959578","doi":"https://doi.org/10.1109/cvprw50498.2020.00152","mag":"3035959578"},"language":"en","primary_location":{"id":"doi:10.1109/cvprw50498.2020.00152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw50498.2020.00152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","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/A5006619341","display_name":"Olga Perepelkina","orcid":"https://orcid.org/0000-0001-9357-8407"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Olga Perepelkina","raw_affiliation_strings":["Neurodata Lab LLC, Miami, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Neurodata Lab LLC, Miami, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051654477","display_name":"Mikhail Artemyev","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mikhail Artemyev","raw_affiliation_strings":["Neurodata Lab LLC, Miami, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Neurodata Lab LLC, Miami, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065089488","display_name":"Marina Churikova","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marina Churikova","raw_affiliation_strings":["Neurodata Lab LLC, Miami, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Neurodata Lab LLC, Miami, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011294395","display_name":"Mikhail Grinenko","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mikhail Grinenko","raw_affiliation_strings":["Neurodata Lab LLC, Miami, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Neurodata Lab LLC, Miami, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.3984,"has_fulltext":false,"cited_by_count":74,"citation_normalized_percentile":{"value":0.92906826,"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":"1163","last_page":"1171"},"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":0.9987000226974487,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9983000159263611,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7872503995895386},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7113664746284485},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.692922055721283},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5384471416473389},{"id":"https://openalex.org/keywords/photoplethysmogram","display_name":"Photoplethysmogram","score":0.5051093697547913},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47614288330078125},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4570392072200775},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41027140617370605},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4093884229660034},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36900416016578674},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.31902337074279785},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.06815648078918457}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7872503995895386},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7113664746284485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.692922055721283},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5384471416473389},{"id":"https://openalex.org/C116390426","wikidata":"https://www.wikidata.org/wiki/Q7187885","display_name":"Photoplethysmogram","level":3,"score":0.5051093697547913},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47614288330078125},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4570392072200775},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41027140617370605},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4093884229660034},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36900416016578674},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.31902337074279785},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.06815648078918457},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvprw50498.2020.00152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw50498.2020.00152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","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":34,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W2012592339","https://openalex.org/W2029745771","https://openalex.org/W2069692225","https://openalex.org/W2083872334","https://openalex.org/W2123649031","https://openalex.org/W2402211617","https://openalex.org/W2461101863","https://openalex.org/W2472200183","https://openalex.org/W2564888233","https://openalex.org/W2612445135","https://openalex.org/W2766766681","https://openalex.org/W2798730128","https://openalex.org/W2806321567","https://openalex.org/W2893517024","https://openalex.org/W2902449706","https://openalex.org/W2903521046","https://openalex.org/W2908176906","https://openalex.org/W2910943657","https://openalex.org/W2958501326","https://openalex.org/W2963351448","https://openalex.org/W2963433879","https://openalex.org/W2980584869","https://openalex.org/W2983650375","https://openalex.org/W2984922178","https://openalex.org/W4297775537","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6737664043","https://openalex.org/W6751633765","https://openalex.org/W6754458465","https://openalex.org/W6756459063","https://openalex.org/W6769642405"],"related_works":["https://openalex.org/W4297152434","https://openalex.org/W2732360296","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Detection":[0],"and":[1,142,165,181,187,189,198],"continuous":[2],"monitoring":[3],"of":[4,13,23,31,48,83,94,170],"heart":[5,46,112,127],"rate":[6,47,113,128],"can":[7,42],"help":[8],"us":[9],"identify":[10],"clinical":[11],"relevance":[12],"some":[14],"cardiac":[15],"symptoms.":[16],"Over":[17],"the":[18,29,32,70,155,190,195,211],"last":[19],"decade,":[20],"a":[21,39,104],"lot":[22],"attention":[24],"has":[25,118],"been":[26,68,119],"paid":[27],"to":[28,124,154],"development":[30],"algorigthms":[33],"for":[34,85,109,184,194],"remote":[35,110],"photoplethysmography":[36],"(rPPG).":[37],"As":[38],"result,":[40],"we":[41,101,134],"now":[43],"accurately":[44,125],"monitor":[45],"still":[49],"sitting":[50],"subjects":[51],"using":[52],"data":[53,84,89,123],"extracted":[54],"from":[55,59,92],"video":[56],"feed.":[57],"Aside":[58],"methods":[60,78],"based":[61],"on":[62,121,210],"hand-crafted":[63],"features,":[64],"there":[65],"have":[66,102,176],"also":[67],"developed":[69,103],"more":[71],"advanced":[72],"learning-based":[73,116],"rPPG":[74,138],"algorithms.":[75],"Deep":[76],"learning":[77],"usually":[79],"require":[80],"large":[81],"amounts":[82],"training,":[86],"however,":[87],"biomedical":[88],"often":[90],"suffers":[91],"lack":[93],"real-life":[95],"data.":[96],"To":[97],"address":[98],"these":[99],"issues,":[100],"HeartTrack":[105,204],"convolutional":[106],"neural":[107,205],"network":[108,206],"video-based":[111],"tracking.":[114],"This":[115],"method":[117],"trained":[120],"synthetic":[122],"estimate":[126],"in":[129,148],"different":[130,168],"conditions.":[131],"Moreover,":[132],"here":[133],"provide":[135],"two":[136],"new":[137,179],"datasets":[139,159,183],"-":[140,144],"MoLi-ppg-1":[141,180],"MoLi-ppg-2":[143,182],"that":[145,151,162],"were":[146,152],"recorded":[147],"complicated":[149],"conditions":[150],"close":[153],"natural":[156],"ones.":[157],"The":[158],"include":[160],"videos":[161],"feature":[163],"moving":[164],"talking":[166],"subjects,":[167],"types":[169],"lighting,":[171],"various":[172],"equipment,":[173],"etc.":[174],"We":[175],"used":[177],"our":[178],"algorithm":[185,196],"training":[186],"testing,":[188],"existing":[191],"UBFCRPPG":[192],"dataset":[193],"testing":[197],"comparison":[199],"with":[200],"other":[201],"approaches.":[202],"Our":[203],"shows":[207],"state-of-the-art":[208],"results":[209],"UBFC-RPPG":[212],"database":[213],"(MAE=2.412,":[214],"RMSE=3.368,":[215],"R=0.983).":[216]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}