{"id":"https://openalex.org/W4389577171","doi":"https://doi.org/10.1109/embc40787.2023.10340100","title":"Continual Learning for Cuffless Blood Pressure Measurement using PPG and ECG Signals","display_name":"Continual Learning for Cuffless Blood Pressure Measurement using PPG and ECG Signals","publication_year":2023,"publication_date":"2023-07-24","ids":{"openalex":"https://openalex.org/W4389577171","doi":"https://doi.org/10.1109/embc40787.2023.10340100","pmid":"https://pubmed.ncbi.nlm.nih.gov/38083321"},"language":"en","primary_location":{"id":"doi:10.1109/embc40787.2023.10340100","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/embc40787.2023.10340100","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 45th Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5063545097","display_name":"Chunlin Zhang","orcid":"https://orcid.org/0000-0003-3957-8603"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chunlin Zhang","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Life Science and Technology,Chengdu,China","School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Life Science and Technology,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100569947","display_name":"Zhan Shen","orcid":"https://orcid.org/0000-0001-8286-5953"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhan Shen","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Life Science and Technology,Chengdu,China","School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Life Science and Technology,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045998203","display_name":"Xiaorong Ding","orcid":"https://orcid.org/0000-0002-3269-2852"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaorong Ding","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Life Science and Technology,Chengdu,China","School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Life Science and Technology,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5063545097"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.2148,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.49489454,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"2023","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":0.9979000091552734,"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":0.9973999857902527,"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":0.9375244379043579},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.644085168838501},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.6367319226264954},{"id":"https://openalex.org/keywords/mean-absolute-error","display_name":"Mean absolute error","score":0.6018239259719849},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5719643831253052},{"id":"https://openalex.org/keywords/blood-pressure","display_name":"Blood pressure","score":0.5694940090179443},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.490149587392807},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47404763102531433},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4523972272872925},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3990921378135681},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.3192426264286041},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.18696853518486023},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16161569952964783},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14504733681678772},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.1390065848827362},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08247911930084229}],"concepts":[{"id":"https://openalex.org/C116390426","wikidata":"https://www.wikidata.org/wiki/Q7187885","display_name":"Photoplethysmogram","level":3,"score":0.9375244379043579},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.644085168838501},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.6367319226264954},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.6018239259719849},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5719643831253052},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.5694940090179443},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.490149587392807},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47404763102531433},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4523972272872925},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3990921378135681},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.3192426264286041},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.18696853518486023},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16161569952964783},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14504733681678772},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.1390065848827362},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08247911930084229},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001794","descriptor_name":"Blood Pressure","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001794","descriptor_name":"Blood Pressure","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001794","descriptor_name":"Blood Pressure","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001794","descriptor_name":"Blood Pressure","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001794","descriptor_name":"Blood Pressure","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001795","descriptor_name":"Blood Pressure Determination","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D001795","descriptor_name":"Blood Pressure Determination","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D001795","descriptor_name":"Blood Pressure Determination","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D001795","descriptor_name":"Blood Pressure Determination","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D001795","descriptor_name":"Blood Pressure Determination","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"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":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D017156","descriptor_name":"Photoplethysmography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D017156","descriptor_name":"Photoplethysmography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D017156","descriptor_name":"Photoplethysmography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D017156","descriptor_name":"Photoplethysmography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D017156","descriptor_name":"Photoplethysmography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc40787.2023.10340100","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/embc40787.2023.10340100","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 45th Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:38083321","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38083321","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":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.5699999928474426,"display_name":"Good health and well-being"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1528687555","https://openalex.org/W2088204643","https://openalex.org/W2396881363","https://openalex.org/W2431637923","https://openalex.org/W2793520628","https://openalex.org/W2899619773","https://openalex.org/W3196722428","https://openalex.org/W4297176686","https://openalex.org/W6755715394"],"related_works":["https://openalex.org/W2905091233","https://openalex.org/W4247388746","https://openalex.org/W2314720829","https://openalex.org/W3178576217","https://openalex.org/W4221063543","https://openalex.org/W4285794683","https://openalex.org/W4385195237","https://openalex.org/W4286256617","https://openalex.org/W4362673848","https://openalex.org/W4310873162"],"abstract_inverted_index":{"Although":[0],"numerous":[1],"studies":[2],"have":[3],"been":[4,168],"conducted":[5],"on":[6,98,138],"cuffless":[7],"blood":[8],"pressure":[9],"(BP)":[10],"estimation":[11,82,127],"using":[12],"machine":[13],"learning":[14,63,69],"methods,":[15],"most":[16],"of":[17,92,107,131,152],"the":[18,36,45,52,93,121,125,146,150],"data-driven":[19],"models":[20,70],"are":[21,71],"static,":[22],"with":[23,83,104,113,141,149,170],"model":[24,43,95,123,159],"parameters":[25],"fixed":[26],"after":[27],"training":[28,53,115,143],"is":[29,33,96],"complete.":[30],"However,":[31],"BP":[32,48,54,80],"dynamic":[34,164],"and":[35,76,86,101,111],"performance":[37],"would":[38],"degrade":[39],"for":[40,78],"a":[41,61,105],"static":[42],"when":[44],"to-be":[46],"predicted":[47],"distribution":[49],"deviates":[50],"from":[51],"distribution.":[55],"In":[56],"this":[57],"paper,":[58],"we":[59],"propose":[60],"continual":[62],"(CL)":[64],"framework":[65],"in":[66,129],"which":[67,166],"deep":[68],"developed":[72],"to":[73,162],"learn":[74],"dynamically":[75],"continuously":[77],"arterial":[79],"(ABP)":[81],"photoplethysmography":[84],"(PPG)":[85],"electrocardiogram":[87],"(ECG)":[88],"waveforms.":[89],"The":[90],"effectiveness":[91],"CL":[94,122,158],"validated":[97],"UCI":[99],"Repository":[100],"MIMIC-III":[102],"database":[103],"total":[106],"132":[108],"individual":[109],"samples,":[110],"compared":[112,140],"conventional":[114,142,171],"method.":[116],"It":[117],"was":[118],"found":[119],"that":[120,157],"improved":[124],"ABP":[126],"accuracy":[128],"terms":[130],"mean":[132],"absolute":[133],"error":[134],"(MAE)":[135],"by":[136],"17.47%":[137],"average":[139],"model.":[144],"Furthermore,":[145],"improvement":[147],"increased":[148],"variability":[151],"ABP.":[153],"These":[154],"results":[155],"demonstrate":[156],"has":[160,167],"potential":[161],"estimate":[163],"ABP,":[165],"challenging":[169],"training.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-23T09:07:50.710637","created_date":"2025-10-10T00:00:00"}
