{"id":"https://openalex.org/W4400131232","doi":"https://doi.org/10.3390/s24134198","title":"Temporal Convolutional Neural Network-Based Prediction of Vascular Health in Elderly Women Using Photoplethysmography-Derived Pulse Wave during Exercise","display_name":"Temporal Convolutional Neural Network-Based Prediction of Vascular Health in Elderly Women Using Photoplethysmography-Derived Pulse Wave during Exercise","publication_year":2024,"publication_date":"2024-06-28","ids":{"openalex":"https://openalex.org/W4400131232","doi":"https://doi.org/10.3390/s24134198","pmid":"https://pubmed.ncbi.nlm.nih.gov/39000977"},"language":"en","primary_location":{"id":"doi:10.3390/s24134198","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24134198","pdf_url":"https://www.mdpi.com/1424-8220/24/13/4198/pdf?version=1719559929","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/1424-8220/24/13/4198/pdf?version=1719559929","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093830074","display_name":"Yue Xiao","orcid":"https://orcid.org/0000-0002-4803-7027"},"institutions":[{"id":"https://openalex.org/I63354593","display_name":"Sichuan Normal University","ror":"https://ror.org/043dxc061","country_code":"CN","type":"education","lineage":["https://openalex.org/I63354593"]},{"id":"https://openalex.org/I87710204","display_name":"Beijing Sport University","ror":"https://ror.org/03w0k0x36","country_code":"CN","type":"education","lineage":["https://openalex.org/I87710204"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Xiao","raw_affiliation_strings":["Chinese Wushu Academy, Beijing Sport University, Beijing 100084, China","School of Physical Educantion and Sports, Sichuan Normal University, Chengdu 610101, China"],"raw_orcid":"https://orcid.org/0000-0002-4803-7027","affiliations":[{"raw_affiliation_string":"Chinese Wushu Academy, Beijing Sport University, Beijing 100084, China","institution_ids":["https://openalex.org/I87710204"]},{"raw_affiliation_string":"School of Physical Educantion and Sports, Sichuan Normal University, Chengdu 610101, China","institution_ids":["https://openalex.org/I63354593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081424082","display_name":"Guixian Wang","orcid":"https://orcid.org/0000-0003-4704-4935"},"institutions":[{"id":"https://openalex.org/I87710204","display_name":"Beijing Sport University","ror":"https://ror.org/03w0k0x36","country_code":"CN","type":"education","lineage":["https://openalex.org/I87710204"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guixian Wang","raw_affiliation_strings":["Chinese Wushu Academy, Beijing Sport University, Beijing 100084, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Wushu Academy, Beijing Sport University, Beijing 100084, China","institution_ids":["https://openalex.org/I87710204"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100616468","display_name":"Haojie Li","orcid":"https://orcid.org/0000-0002-4997-9083"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haojie Li","raw_affiliation_strings":["School of Physical Educantion and Sports, Beijing Normal University, Beijing 100875, China"],"raw_orcid":"https://orcid.org/0000-0002-4997-9083","affiliations":[{"raw_affiliation_string":"School of Physical Educantion and Sports, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081424082"],"corresponding_institution_ids":["https://openalex.org/I87710204"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.168,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.44062695,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"24","issue":"13","first_page":"4198","last_page":"4198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9980000257492065,"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"}},{"id":"https://openalex.org/T10924","display_name":"Cardiovascular Health and Disease Prevention","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":0.9645540118217468},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6785077452659607},{"id":"https://openalex.org/keywords/pulse-wave-analysis","display_name":"Pulse Wave Analysis","score":0.674156665802002},{"id":"https://openalex.org/keywords/pulse","display_name":"Pulse (music)","score":0.5198907852172852},{"id":"https://openalex.org/keywords/pulse-wave-velocity","display_name":"Pulse wave velocity","score":0.517069399356842},{"id":"https://openalex.org/keywords/pulse-wave","display_name":"Pulse wave","score":0.49619418382644653},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.478397011756897},{"id":"https://openalex.org/keywords/cardiovascular-health","display_name":"Cardiovascular health","score":0.47337907552719116},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40595874190330505},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3877618908882141},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3520281910896301},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.2465747892856598},{"id":"https://openalex.org/keywords/blood-pressure","display_name":"Blood pressure","score":0.16722425818443298},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15124070644378662},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.11623144149780273}],"concepts":[{"id":"https://openalex.org/C116390426","wikidata":"https://www.wikidata.org/wiki/Q7187885","display_name":"Photoplethysmogram","level":3,"score":0.9645540118217468},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6785077452659607},{"id":"https://openalex.org/C2908916285","wikidata":"https://www.wikidata.org/wiki/Q2118022","display_name":"Pulse Wave Analysis","level":4,"score":0.674156665802002},{"id":"https://openalex.org/C2780167933","wikidata":"https://www.wikidata.org/wiki/Q1550652","display_name":"Pulse (music)","level":3,"score":0.5198907852172852},{"id":"https://openalex.org/C2778319312","wikidata":"https://www.wikidata.org/wiki/Q2118022","display_name":"Pulse wave velocity","level":3,"score":0.517069399356842},{"id":"https://openalex.org/C172321821","wikidata":"https://www.wikidata.org/wiki/Q7259685","display_name":"Pulse wave","level":3,"score":0.49619418382644653},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.478397011756897},{"id":"https://openalex.org/C3018284874","wikidata":"https://www.wikidata.org/wiki/Q389735","display_name":"Cardiovascular health","level":3,"score":0.47337907552719116},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40595874190330505},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3877618908882141},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3520281910896301},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.2465747892856598},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.16722425818443298},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15124070644378662},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.11623144149780273},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C134652429","wikidata":"https://www.wikidata.org/wiki/Q1052698","display_name":"Jitter","level":2,"score":0.0},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","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":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003430","descriptor_name":"Cross-Sectional Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003430","descriptor_name":"Cross-Sectional Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003430","descriptor_name":"Cross-Sectional Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003430","descriptor_name":"Cross-Sectional Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","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":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015444","descriptor_name":"Exercise","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D015444","descriptor_name":"Exercise","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D015444","descriptor_name":"Exercise","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D015444","descriptor_name":"Exercise","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"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},{"descriptor_ui":"D063177","descriptor_name":"Pulse Wave Analysis","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D063177","descriptor_name":"Pulse Wave Analysis","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D063177","descriptor_name":"Pulse Wave Analysis","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D063177","descriptor_name":"Pulse Wave Analysis","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.3390/s24134198","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24134198","pdf_url":"https://www.mdpi.com/1424-8220/24/13/4198/pdf?version=1719559929","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:39000977","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39000977","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:pubmedcentral.nih.gov:11244390","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11244390","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11244390/pdf/sensors-24-04198.pdf","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"},{"id":"pmh:oai:doaj.org/article:7705ea3dbdf54815b42580ee3278959b","is_oa":false,"landing_page_url":"https://doaj.org/article/7705ea3dbdf54815b42580ee3278959b","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 24, Iss 13, p 4198 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s24134198","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24134198","pdf_url":"https://www.mdpi.com/1424-8220/24/13/4198/pdf?version=1719559929","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":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400131232.pdf","grobid_xml":"https://content.openalex.org/works/W4400131232.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1982091872","https://openalex.org/W1997383259","https://openalex.org/W2018410552","https://openalex.org/W2030883271","https://openalex.org/W2033587261","https://openalex.org/W2066932506","https://openalex.org/W2124653687","https://openalex.org/W2141240913","https://openalex.org/W2807710063","https://openalex.org/W2896737926","https://openalex.org/W2903178575","https://openalex.org/W2947915417","https://openalex.org/W3033516560","https://openalex.org/W4200463719","https://openalex.org/W4220786439","https://openalex.org/W4282978129","https://openalex.org/W4292847954","https://openalex.org/W4313279534","https://openalex.org/W4322748740","https://openalex.org/W4327730813","https://openalex.org/W4328049748","https://openalex.org/W4361270040","https://openalex.org/W4366463965","https://openalex.org/W4386566012","https://openalex.org/W4387223393","https://openalex.org/W4387717386","https://openalex.org/W4390403702","https://openalex.org/W4391262219","https://openalex.org/W4392244965","https://openalex.org/W4394691350","https://openalex.org/W6804848810","https://openalex.org/W6851591508"],"related_works":["https://openalex.org/W3152731300","https://openalex.org/W638376227","https://openalex.org/W2120037269","https://openalex.org/W2043326433","https://openalex.org/W4376105416","https://openalex.org/W2390282139","https://openalex.org/W2412418861","https://openalex.org/W2028927310","https://openalex.org/W332615335","https://openalex.org/W2898782655"],"abstract_inverted_index":{"(1)":[0],"Background:":[1],"The":[2,46,139,181],"objective":[3],"of":[4,14,33,83,122,141,144,152,169,183,199,218,236,240],"this":[5],"study":[6,47],"was":[7,55,78,97,101,164],"to":[8,103],"predict":[9],"the":[10,44,75,81,131,142,150,153,159,191,195,216,232,237],"vascular":[11,196,238],"health":[12,197,239],"status":[13,198],"elderly":[15,36,200,241],"women":[16,37,201],"during":[17,187],"exercise":[18,95,188,219],"using":[19,58,67],"pulse":[20,184,220],"wave":[21,63,185,221],"data":[22,186,222],"and":[23,71,111,125,134,161,175,209,234],"Temporal":[24],"Convolutional":[25],"Neural":[26],"Networks":[27],"(TCN);":[28],"(2)":[29],"Methods:":[30],"A":[31,92,99],"total":[32],"492":[34],"healthy":[35],"aged":[38],"60-75":[39],"years":[40],"were":[41,65],"recruited":[42],"for":[43,193,231],"study.":[45],"utilized":[48],"a":[49,84],"cross-sectional":[50],"design.":[51],"Vascular":[52],"endothelial":[53],"function":[54],"assessed":[56],"non-invasively":[57],"Flow-Mediated":[59],"Dilation":[60],"(FMD).":[61],"Pulse":[62],"characteristics":[64],"quantified":[66],"photoplethysmography":[68],"(PPG)":[69],"sensors,":[70],"motion-induced":[72],"noise":[73],"in":[74,127,155,206],"PPG":[76],"signals":[77],"mitigated":[79],"through":[80],"application":[82],"recursive":[85],"least":[86],"squares":[87],"(RLS)":[88],"adaptive":[89],"filtering":[90],"algorithm.":[91],"fixed-load":[93],"cycling":[94],"protocol":[96],"employed.":[98],"TCN":[100,117,154,192,224],"constructed":[102],"classify":[104],"flow-mediated":[105],"dilation":[106],"(FMD)":[107],"into":[108],"\"optimal\",":[109,132],"\"impaired\",":[110,133],"\"at":[112,135],"risk\"":[113,136],"levels;":[114],"(3)":[115],"Results:":[116],"achieved":[118],"an":[119,228],"average":[120],"accuracy":[121,151],"79.3%,":[123],"84.8%,":[124],"83.2%":[126],"predicting":[128,156,194,207],"FMD":[129,157,211],"at":[130,158],"levels,":[137],"respectively.":[138],"results":[140],"analysis":[143],"variance":[145],"(ANOVA)":[146],"comparison":[147],"demonstrated":[148,202],"that":[149,168,215],"impaired":[160,208],"at-risk":[162,210],"levels":[163],"significantly":[165],"higher":[166],"than":[167],"Long":[170],"Short-Term":[171],"Memory":[172],"(LSTM)":[173],"networks":[174],"Random":[176],"Forest":[177],"algorithms;":[178],"(4)":[179],"Conclusions:":[180],"use":[182],"combined":[189],"with":[190,223],"high":[203],"accuracy,":[204],"particularly":[205],"levels.":[212],"This":[213],"indicates":[214],"integration":[217],"can":[225],"serve":[226],"as":[227],"effective":[229],"tool":[230],"assessment":[233],"monitoring":[235],"women.":[242]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
