{"id":"https://openalex.org/W3012297411","doi":"https://doi.org/10.1109/access.2020.2981956","title":"Deep Learning for Heart Rate Estimation From Reflectance Photoplethysmography With Acceleration Power Spectrum and Acceleration Intensity","display_name":"Deep Learning for Heart Rate Estimation From Reflectance Photoplethysmography With Acceleration Power Spectrum and Acceleration Intensity","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3012297411","doi":"https://doi.org/10.1109/access.2020.2981956","mag":"3012297411"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2981956","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2981956","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09042276.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09042276.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026613707","display_name":"Heewon \ufeffChung","orcid":"https://orcid.org/0000-0002-4039-1419"},"institutions":[{"id":"https://openalex.org/I77079311","display_name":"Wonkwang University","ror":"https://ror.org/006776986","country_code":"KR","type":"education","lineage":["https://openalex.org/I77079311"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Heewon Chung","raw_affiliation_strings":["Department of Biomedical Engineering, Wonkwang University College of Medicine, Iksan, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-4039-1419","affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Wonkwang University College of Medicine, Iksan, South Korea","institution_ids":["https://openalex.org/I77079311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101545215","display_name":"Hoon Ko","orcid":"https://orcid.org/0000-0001-7807-215X"},"institutions":[{"id":"https://openalex.org/I77079311","display_name":"Wonkwang University","ror":"https://ror.org/006776986","country_code":"KR","type":"education","lineage":["https://openalex.org/I77079311"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hoon Ko","raw_affiliation_strings":["Department of Biomedical Engineering, Wonkwang University College of Medicine, Iksan, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-7807-215X","affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Wonkwang University College of Medicine, Iksan, South Korea","institution_ids":["https://openalex.org/I77079311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055721024","display_name":"Hooseok Lee","orcid":"https://orcid.org/0000-0003-1410-425X"},"institutions":[{"id":"https://openalex.org/I77079311","display_name":"Wonkwang University","ror":"https://ror.org/006776986","country_code":"KR","type":"education","lineage":["https://openalex.org/I77079311"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hooseok Lee","raw_affiliation_strings":["Department of Biomedical Engineering, Wonkwang University College of Medicine, Iksan, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-1410-425X","affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Wonkwang University College of Medicine, Iksan, South Korea","institution_ids":["https://openalex.org/I77079311"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100746133","display_name":"Jinseok Lee","orcid":"https://orcid.org/0000-0002-8580-490X"},"institutions":[{"id":"https://openalex.org/I77079311","display_name":"Wonkwang University","ror":"https://ror.org/006776986","country_code":"KR","type":"education","lineage":["https://openalex.org/I77079311"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jinseok Lee","raw_affiliation_strings":["Department of Biomedical Engineering, Wonkwang University College of Medicine, Iksan, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-8580-490X","affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Wonkwang University College of Medicine, Iksan, South Korea","institution_ids":["https://openalex.org/I77079311"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5026613707"],"corresponding_institution_ids":["https://openalex.org/I77079311"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.2227,"has_fulltext":true,"cited_by_count":46,"citation_normalized_percentile":{"value":0.92251131,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"63390","last_page":"63402"},"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":0.9986000061035156,"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/T11700","display_name":"Hemodynamic Monitoring and Therapy","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/softmax-function","display_name":"Softmax function","score":0.8289451599121094},{"id":"https://openalex.org/keywords/photoplethysmogram","display_name":"Photoplethysmogram","score":0.7952128648757935},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7873989343643188},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.620780348777771},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5979124307632446},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.5451412200927734},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.531827986240387},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5045129060745239},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.44989603757858276},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44809678196907043},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.41857296228408813},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.378815621137619},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.17887139320373535},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12484940886497498},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11365953087806702},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09497752785682678}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.8289451599121094},{"id":"https://openalex.org/C116390426","wikidata":"https://www.wikidata.org/wiki/Q7187885","display_name":"Photoplethysmogram","level":3,"score":0.7952128648757935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7873989343643188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.620780348777771},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5979124307632446},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.5451412200927734},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.531827986240387},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5045129060745239},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.44989603757858276},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44809678196907043},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.41857296228408813},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.378815621137619},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.17887139320373535},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12484940886497498},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11365953087806702},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09497752785682678},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2981956","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2981956","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09042276.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2849484a65844b02aace4e52f72a9326","is_oa":true,"landing_page_url":"https://doaj.org/article/2849484a65844b02aace4e52f72a9326","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 63390-63402 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2981956","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2981956","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09042276.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G598488457","display_name":null,"funder_award_id":"2020R1A2C1014829","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G7113667841","display_name":null,"funder_award_id":"NRF-2020R1A2C1014829","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G8783856367","display_name":null,"funder_award_id":"NRF-2015M3A9D7067215","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3012297411.pdf","grobid_xml":"https://content.openalex.org/works/W3012297411.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1849865010","https://openalex.org/W1910786341","https://openalex.org/W2005741801","https://openalex.org/W2037549735","https://openalex.org/W2091314241","https://openalex.org/W2151713296","https://openalex.org/W2204117563","https://openalex.org/W2288945889","https://openalex.org/W2531409750","https://openalex.org/W2571147762","https://openalex.org/W2592075940","https://openalex.org/W2609904211","https://openalex.org/W2610645870","https://openalex.org/W2763068163","https://openalex.org/W2767834540","https://openalex.org/W2772327757","https://openalex.org/W2789746872","https://openalex.org/W2891220451","https://openalex.org/W2892061408","https://openalex.org/W2910830939","https://openalex.org/W2913185942","https://openalex.org/W2932441661","https://openalex.org/W2942813403","https://openalex.org/W2962182608","https://openalex.org/W2979595423","https://openalex.org/W3098824483"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W3090555870","https://openalex.org/W4226420367","https://openalex.org/W2962876041","https://openalex.org/W2732360296","https://openalex.org/W3022820045","https://openalex.org/W1994871954","https://openalex.org/W2899027234"],"abstract_inverted_index":{"Objective:":[0],"A":[1],"wearable":[2],"reflectance-type":[3],"photoplethysmography":[4],"(PPG)":[5],"sensor":[6,28],"can":[7],"be":[8],"incorporated":[9],"in":[10,37],"a":[11,47,66,102,129,144],"watch":[12],"or":[13],"band":[14],"to":[15,24,31,54,122,132],"provide":[16],"instantaneous":[17],"heart":[18],"rates":[19],"(HRs)":[20],"with":[21,118,211],"minimum":[22],"inconvenience":[23],"users.":[25],"However,":[26],"the":[27,108,112,119,123,134,139,173,182,189,197,209,221],"is":[29],"sensitive":[30],"motion":[32],"artifacts":[33],"(MAs),":[34],"which":[35],"results":[36],"inaccurate":[38],"HR":[39,57,79,141],"estimation.":[40,80],"To":[41],"address":[42],"this":[43],"problem,":[44],"we":[45],"propose":[46,65],"new":[48,67,130],"neural":[49,69],"network":[50,70],"for":[51,78,171,181,188,200],"deep":[52,68],"learning":[53],"ensure":[55],"accurate":[56,201],"estimation":[58,202],"even":[59,213],"during":[60,214],"intensive":[61,215],"exercise.":[62],"Methods:":[63],"We":[64,126,148],"based":[71],"on":[72],"multiclass":[73],"and":[74,96,114,153,175,185],"non-uniform":[75],"multilabel":[76],"classification":[77],"It":[81,206],"comprises":[82],"of":[83,166,203],"two":[84,87],"convolutional":[85],"layers,":[86,92],"long":[88],"short-term":[89],"memory":[90],"(LSTM)":[91],"one":[93],"concatenation":[94],"layer,":[95],"three":[97],"fully":[98],"connected":[99],"layers":[100],"including":[101],"softmax.":[103],"The":[104,159,193],"proposed":[105,160,194],"model":[106,161,195],"feeds":[107],"power":[109],"spectra":[110],"from":[111],"PPG":[113,224],"acceleration":[115,120],"signals":[116,225],"along":[117],"intensity":[121],"input":[124],"layer.":[125],"also":[127],"present":[128],"scheme":[131],"evaluate":[133],"loss":[135],"value":[136,142],"by":[137,220,229],"modifying":[138],"true":[140],"into":[143],"Gaussian":[145],"distribution.":[146],"Results:":[147],"used":[149],"48":[150],"training":[151,174,183],"datasets":[152,177],"evaluated":[154],"23":[155],"isolated":[156],"testing":[157],"datasets.":[158],"exhibited":[162],"average":[163],"absolute":[164],"error":[165],"less":[167],"than":[168],"1.5":[169],"bpm":[170,180,187],"all":[172],"test":[176,190],"-":[178],"1.09":[179],"dataset":[184],"1.46":[186],"dataset.":[191],"Conclusion:":[192],"outperforms":[196],"state-of-the-art":[198],"methods":[199],"HR.":[204],"Significance:":[205],"precisely":[207],"estimates":[208],"HRs":[210],"robustness":[212],"physical":[216],"exercise,":[217],"as":[218],"evidenced":[219],"accuracy":[222],"when":[223],"are":[226],"severely":[227],"corrupted":[228],"MAs.":[230]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":9}],"updated_date":"2026-05-24T08:33:08.758527","created_date":"2025-10-10T00:00:00"}
