{"id":"https://openalex.org/W3016504312","doi":"https://doi.org/10.3390/s20082338","title":"End-To-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism","display_name":"End-To-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism","publication_year":2020,"publication_date":"2020-04-20","ids":{"openalex":"https://openalex.org/W3016504312","doi":"https://doi.org/10.3390/s20082338","mag":"3016504312","pmid":"https://pubmed.ncbi.nlm.nih.gov/32325970"},"language":"en","primary_location":{"id":"doi:10.3390/s20082338","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20082338","pdf_url":"https://www.mdpi.com/1424-8220/20/8/2338/pdf?version=1587891728","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/20/8/2338/pdf?version=1587891728","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076807189","display_name":"Heesang Eom","orcid":"https://orcid.org/0000-0001-7418-5042"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Heesang Eom","raw_affiliation_strings":["Department of Computer Engineering, Kwangwoon University, Seoul 01897, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Kwangwoon University, Seoul 01897, Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101533075","display_name":"Dongseok Lee","orcid":"https://orcid.org/0000-0002-6960-9127"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dongseok Lee","raw_affiliation_strings":["Interdisciplinary Program in Bioengineering, Seoul National University, Seoul 03080, Korea"],"raw_orcid":"https://orcid.org/0000-0002-6960-9127","affiliations":[{"raw_affiliation_string":"Interdisciplinary Program in Bioengineering, Seoul National University, Seoul 03080, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070678616","display_name":"Seungwoo Han","orcid":"https://orcid.org/0000-0003-1834-076X"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seungwoo Han","raw_affiliation_strings":["Department of Intelligent Information System and Embedded Software Engineering, Kwangwoon University, Seoul 01897, Korea"],"raw_orcid":"https://orcid.org/0000-0003-1834-076X","affiliations":[{"raw_affiliation_string":"Department of Intelligent Information System and Embedded Software Engineering, Kwangwoon University, Seoul 01897, Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026447214","display_name":"Yuli Sun Hariyani","orcid":"https://orcid.org/0000-0003-0618-3082"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]},{"id":"https://openalex.org/I862893732","display_name":"Telkom University","ror":"https://ror.org/0004wsx81","country_code":"ID","type":"education","lineage":["https://openalex.org/I862893732"]}],"countries":["ID","KR"],"is_corresponding":false,"raw_author_name":"Yuli Sun Hariyani","raw_affiliation_strings":["Department of Computer Engineering, Kwangwoon University, Seoul 01897, Korea","School of Applied Science, Telkom University, Bandung 40257, Indonesia"],"raw_orcid":"https://orcid.org/0000-0003-0618-3082","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Kwangwoon University, Seoul 01897, Korea","institution_ids":["https://openalex.org/I161024014"]},{"raw_affiliation_string":"School of Applied Science, Telkom University, Bandung 40257, Indonesia","institution_ids":["https://openalex.org/I862893732"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110168577","display_name":"Yonggyu Lim","orcid":null},"institutions":[{"id":"https://openalex.org/I9507","display_name":"Sangji University","ror":"https://ror.org/01gqe3t73","country_code":"KR","type":"education","lineage":["https://openalex.org/I9507"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yonggyu Lim","raw_affiliation_strings":["Department of Oriental Biomedical Engineering, Sangji University, Wonju 26339, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Oriental Biomedical Engineering, Sangji University, Wonju 26339, Korea","institution_ids":["https://openalex.org/I9507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081832761","display_name":"Illsoo Sohn","orcid":"https://orcid.org/0000-0003-3943-4781"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Illsoo Sohn","raw_affiliation_strings":["Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul 01811, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul 01811, Korea","institution_ids":["https://openalex.org/I118373667"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065697354","display_name":"Kwangsuk Park","orcid":"https://orcid.org/0000-0002-2247-3795"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Kwangsuk Park","raw_affiliation_strings":["Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul 03080, Korea","Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul 03080, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul 03080, Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul 03080, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072429332","display_name":"Cheolsoo Park","orcid":"https://orcid.org/0000-0001-8042-007X"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Cheolsoo Park","raw_affiliation_strings":["Department of Computer Engineering, Kwangwoon University, Seoul 01897, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Kwangwoon University, Seoul 01897, Korea","institution_ids":["https://openalex.org/I161024014"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5065697354","https://openalex.org/A5072429332"],"corresponding_institution_ids":["https://openalex.org/I139264467","https://openalex.org/I161024014"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":6.7013,"has_fulltext":false,"cited_by_count":136,"citation_normalized_percentile":{"value":0.98026378,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"20","issue":"8","first_page":"2338","last_page":"2338"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9998999834060669,"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":0.9998999834060669,"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.9984999895095825,"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/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9980000257492065,"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":0.8655754327774048},{"id":"https://openalex.org/keywords/blood-pressure","display_name":"Blood pressure","score":0.610908031463623},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5288637280464172},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5258712768554688},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5112652778625488},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5068348050117493},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5059680342674255},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4882366955280304},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.472484290599823},{"id":"https://openalex.org/keywords/mean-absolute-error","display_name":"Mean absolute error","score":0.4359036386013031},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3575546145439148},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.292252779006958},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25949785113334656},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21116140484809875},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.20543798804283142},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.17269456386566162},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.16125574707984924},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08933743834495544}],"concepts":[{"id":"https://openalex.org/C116390426","wikidata":"https://www.wikidata.org/wiki/Q7187885","display_name":"Photoplethysmogram","level":3,"score":0.8655754327774048},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.610908031463623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5288637280464172},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5258712768554688},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5112652778625488},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5068348050117493},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5059680342674255},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4882366955280304},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.472484290599823},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.4359036386013031},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3575546145439148},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.292252779006958},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25949785113334656},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21116140484809875},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20543798804283142},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.17269456386566162},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.16125574707984924},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08933743834495544},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001450","descriptor_name":"Ballistocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001450","descriptor_name":"Ballistocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001450","descriptor_name":"Ballistocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001450","descriptor_name":"Ballistocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001794","descriptor_name":"Blood Pressure","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D001794","descriptor_name":"Blood Pressure","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D001794","descriptor_name":"Blood Pressure","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D001794","descriptor_name":"Blood Pressure","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016014","descriptor_name":"Linear Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016014","descriptor_name":"Linear Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016014","descriptor_name":"Linear Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016014","descriptor_name":"Linear Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D063177","descriptor_name":"Pulse Wave Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D063177","descriptor_name":"Pulse Wave Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D063177","descriptor_name":"Pulse Wave Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D063177","descriptor_name":"Pulse Wave Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.3390/s20082338","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20082338","pdf_url":"https://www.mdpi.com/1424-8220/20/8/2338/pdf?version=1587891728","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:32325970","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32325970","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:f97997736a034404a4a3d95d96263bbe","is_oa":true,"landing_page_url":"https://doaj.org/article/f97997736a034404a4a3d95d96263bbe","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":"Sensors, Vol 20, Iss 8, p 2338 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/20/8/2338/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s20082338","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7219235","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7219235","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s20082338","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20082338","pdf_url":"https://www.mdpi.com/1424-8220/20/8/2338/pdf?version=1587891728","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3188333454","display_name":null,"funder_award_id":"2017R1A5A1015596","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1514535095","https://openalex.org/W1686810756","https://openalex.org/W1902237438","https://openalex.org/W1924770834","https://openalex.org/W1933258993","https://openalex.org/W1981246897","https://openalex.org/W2006359998","https://openalex.org/W2008268810","https://openalex.org/W2017271435","https://openalex.org/W2021674224","https://openalex.org/W2052434974","https://openalex.org/W2064675550","https://openalex.org/W2088204643","https://openalex.org/W2101739008","https://openalex.org/W2107878631","https://openalex.org/W2133564696","https://openalex.org/W2133750711","https://openalex.org/W2157331557","https://openalex.org/W2162273778","https://openalex.org/W2162800060","https://openalex.org/W2167925220","https://openalex.org/W2194187530","https://openalex.org/W2201092681","https://openalex.org/W2338236284","https://openalex.org/W2431637923","https://openalex.org/W2586246322","https://openalex.org/W2626778328","https://openalex.org/W2774336996","https://openalex.org/W2784502443","https://openalex.org/W2793399999","https://openalex.org/W2793412197","https://openalex.org/W2793520628","https://openalex.org/W2806806521","https://openalex.org/W2884376066","https://openalex.org/W2889838428","https://openalex.org/W2891875385","https://openalex.org/W2901061692","https://openalex.org/W2912902500","https://openalex.org/W2916816078","https://openalex.org/W2944452033","https://openalex.org/W2949117887","https://openalex.org/W2949335953","https://openalex.org/W2950635152","https://openalex.org/W2962215218","https://openalex.org/W2963532813","https://openalex.org/W2963712527","https://openalex.org/W2964267916","https://openalex.org/W2965846681","https://openalex.org/W3140994876","https://openalex.org/W6679758355"],"related_works":["https://openalex.org/W4247388746","https://openalex.org/W2314720829","https://openalex.org/W4285794683","https://openalex.org/W3178576217","https://openalex.org/W4221063543","https://openalex.org/W4385195237","https://openalex.org/W4286256617","https://openalex.org/W4310873162","https://openalex.org/W4318676890","https://openalex.org/W121055840"],"abstract_inverted_index":{"Blood":[0],"pressure":[1],"(BP)":[2],"is":[3,17],"a":[4,67,71,85],"vital":[5],"sign":[6],"that":[7,104],"provides":[8],"fundamental":[9],"health":[10],"information":[11],"regarding":[12],"patients.":[13],"Continuous":[14],"BP":[15,28,55,158,167,171,221],"monitoring":[16,29],"important":[18],"for":[19,165,194,220],"patients":[20],"with":[21,115,204],"hypertension.":[22],"Various":[23],"studies":[24],"have":[25],"proposed":[26,63,214],"cuff-less":[27],"methods":[30],"using":[31,42,58,88,131],"pulse":[32,132],"transit":[33,133],"time.":[34],"We":[35],"propose":[36],"an":[37,77,217],"end-to-end":[38],"deep":[39],"learning":[40],"architecture":[41],"only":[43],"raw":[44],"signals":[45],"without":[46],"the":[47,54,59,89,97,102,109,113,116,156,183,201,210,213],"process":[48],"of":[49,66,91,96,108,138,155,212],"extracting":[50],"features":[51],"to":[52,101],"improve":[53],"estimation":[56],"performance":[57,95,121],"attention":[60,78,117],"mechanism.":[61,79],"The":[62,80,94,151,174,207],"model":[64,81,98,103,114,215],"consisted":[65],"convolutional":[68],"neural":[69],"network,":[70],"bidirectional":[72],"gated":[73],"recurrent":[74],"unit,":[75],"and":[76,112,143,146,162,169,180,182,190,196],"was":[82,99,159],"trained":[83],"by":[84],"calibration-based":[86],"method,":[87],"data":[90],"each":[92,106],"subject.":[93],"compared":[100],"used":[105],"combination":[107],"three":[110],"signals,":[111],"mechanism":[118],"showed":[119],"better":[120],"than":[122],"other":[123],"state-of-the-art":[124],"methods,":[125],"including":[126],"conventional":[127],"linear":[128],"regression":[129],"method":[130],"time":[134],"(PTT).":[135],"A":[136],"total":[137],"15":[139],"subjects":[140],"were":[141,149,178,186],"recruited,":[142],"electrocardiogram,":[144],"ballistocardiogram,":[145],"photoplethysmogram":[147],"levels":[148],"measured.":[150],"95%":[152],"confidence":[153],"interval":[154],"reference":[157],"[86.34,":[160],"143.74]":[161],"[51.28,":[163],"88.74]":[164],"systolic":[166],"(SBP)":[168],"diastolic":[170],"(DBP),":[172],"respectively.":[173,198],"R":[175],"2":[176],"values":[177,185],"0.52":[179],"0.49,":[181],"mean-absolute-error":[184],"4.06":[187],"\u00b1":[188,192],"4.04":[189],"3.33":[191],"3.42":[193],"SBP":[195],"DBP,":[197],"In":[199],"addition,":[200],"results":[202,208],"complied":[203],"global":[205],"standards.":[206],"show":[209],"applicability":[211],"as":[216],"analytical":[218],"metric":[219],"estimation.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":32},{"year":2022,"cited_by_count":26},{"year":2021,"cited_by_count":29},{"year":2020,"cited_by_count":4}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}