{"id":"https://openalex.org/W7204267483","doi":"https://doi.org/10.5573/ieiespc.2026.15.4.512","title":"Blood Pressure Estimation Using Graph Convolutional Neural Networks with Dynamic Adjacency Matrix","display_name":"Blood Pressure Estimation Using Graph Convolutional Neural Networks with Dynamic Adjacency Matrix","publication_year":2026,"publication_date":"2026-08-27","ids":{"openalex":"https://openalex.org/W7204267483","doi":"https://doi.org/10.5573/ieiespc.2026.15.4.512"},"language":"en","primary_location":{"id":"doi:10.5573/ieiespc.2026.15.4.512","doi":"https://doi.org/10.5573/ieiespc.2026.15.4.512","is_oa":false,"landing_page_url":"https://doi.org/10.5573/ieiespc.2026.15.4.512","pdf_url":null,"source":{"id":"https://openalex.org/S2765077331","display_name":"IEIE Transactions on Smart Processing and Computing","issn_l":"2287-5255","issn":["2287-5255"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","kci-registered","poland-20","russia-white-list-4"],"host_organization":"https://openalex.org/P4366305964","host_organization_name":"Institute of Electronics Engineers of Korea","host_organization_lineage":["https://openalex.org/P4366305964"],"host_organization_lineage_names":["Institute of Electronics Engineers of Korea"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEIE Transactions on Smart Processing & Computing","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W7204267483"],"child_works_count":0,"type":"article","is_traditional":true,"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/A5002719761","display_name":"Youngshin Kang","orcid":"https://orcid.org/0000-0002-0573-7007","observed_orcids":["https://orcid.org/0000-0002-0573-7007","https://orcid.org/0000-0002-6023-1009"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Youngshin Kang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135898371","display_name":"Cheolsoo Park","orcid":"https://orcid.org/0000-0001-8042-007X","observed_orcids":["https://orcid.org/0000-0001-8042-007X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheolsoo Park","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":"4","first_page":"512","last_page":"517"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9990000128746033,"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":0.9990000128746033,"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":0.00019999999494757503,"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/T10924","display_name":"Cardiovascular Health and Disease Prevention","score":9.999999747378752e-05,"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/blood-pressure-estimation","display_name":"blood pressure estimation","score":0.9869999885559082},{"id":"https://openalex.org/keywords/graph-convolutional-networks","display_name":"graph convolutional networks","score":0.9440000057220459},{"id":"https://openalex.org/keywords/dynamic-adjacency-matrix","display_name":"dynamic adjacency matrix","score":0.9900000095367432},{"id":"https://openalex.org/keywords/ballistocardiography","display_name":"ballistocardiography","score":0.8679999709129333},{"id":"https://openalex.org/keywords/photoplethysmogram","display_name":"photoplethysmogram","score":0.9890000224113464},{"id":"https://openalex.org/keywords/electrocardiography","display_name":"electrocardiogram","score":1.0},{"id":"https://openalex.org/keywords/noninvasive-blood-pressure-monitoring","display_name":"non-invasive blood pressure monitoring","score":0.902999997138977},{"id":"https://openalex.org/keywords/physiological-signal-fusion","display_name":"physiological signal fusion","score":0.6890000104904175},{"id":"https://openalex.org/keywords/continuous-blood-pressure-monitoring","display_name":"continuous blood pressure monitoring","score":0.6769999861717224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8424999713897705},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.6972000002861023},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6958000063896179},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6237000226974487},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5562999844551086},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4821000099182129},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44020000100135803},{"id":"https://openalex.org/C110484373","wikidata":"https://www.wikidata.org/wiki/Q264398","display_name":"Adjacency list","level":2,"score":0.4336000084877014},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.42160001397132874},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3337000012397766},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2973000109195709},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.25609999895095825}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5573/ieiespc.2026.15.4.512","doi":"https://doi.org/10.5573/ieiespc.2026.15.4.512","is_oa":false,"landing_page_url":"https://doi.org/10.5573/ieiespc.2026.15.4.512","pdf_url":null,"source":{"id":"https://openalex.org/S2765077331","display_name":"IEIE Transactions on Smart Processing and Computing","issn_l":"2287-5255","issn":["2287-5255"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","kci-registered","poland-20","russia-white-list-4"],"host_organization":"https://openalex.org/P4366305964","host_organization_name":"Institute of Electronics Engineers of Korea","host_organization_lineage":["https://openalex.org/P4366305964"],"host_organization_lineage_names":["Institute of Electronics Engineers of Korea"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEIE Transactions on Smart Processing & Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.8560000061988831,"id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7163709169","https://openalex.org/W7163403635","https://openalex.org/W4398756472","https://openalex.org/W7167579211","https://openalex.org/W4367302321","https://openalex.org/W4416578561","https://openalex.org/W2440585849","https://openalex.org/W7117513329","https://openalex.org/W7154167683","https://openalex.org/W4389263045"],"abstract_inverted_index":{"The":[0,93],"estimation":[1,36],"of":[2,15,59],"blood":[3,16,34,109],"pressure":[4,17,35,110],"using":[5],"pulse":[6,42],"transit":[7,43],"time":[8,44],"is":[9,77],"critical":[10],"for":[11,33,72,105],"the":[12,25,57,69,73,86],"continuous":[13],"monitoring":[14],"during":[18],"our":[19,97],"daily":[20],"lives.":[21],"This":[22],"study":[23],"addresses":[24],"challenge":[26],"by":[27],"introducing":[28],"a":[29],"novel,":[30],"non-invasive":[31,108],"approach":[32],"that":[37,55,96],"does":[38],"not":[39],"rely":[40],"on":[41],"(PTT).":[45],"Instead,":[46],"we":[47],"propose":[48],"an":[49],"innovative":[50],"graph-based":[51,98],"neural":[52,75,99],"network":[53,100],"architecture":[54],"leverages":[56],"interconnectedness":[58],"multiple":[60],"physiological":[61,87],"signals,":[62,88],"specifically":[63],"ballistocardiogram,":[64],"photoplethysmogram,":[65],"and":[66,81,91],"electrocardiogram.":[67],"Specifically,":[68],"adjacency":[70],"matrix":[71],"graph":[74],"networks":[76],"constructed":[78],"with":[79],"one-way":[80],"two-way":[82],"directional":[83],"relationships":[84],"among":[85],"Euclidean":[89],"distance,":[90],"causality.":[92],"findings":[94],"suggest":[95],"model":[101],"holds":[102],"significant":[103],"potential":[104],"enhancing":[106],"continuous,":[107],"monitoring,":[111],"thereby":[112],"contributing":[113],"to":[114],"better":[115],"cardiovascular":[116],"health":[117],"management":[118],"in":[119],"everyday":[120],"life.":[121]},"counts_by_year":[],"updated_date":"2026-09-24T07:57:37.273135","created_date":"2026-08-27T00:00:00"}