{"id":"https://openalex.org/W2938092922","doi":"https://doi.org/10.1109/ccis.2018.8691328","title":"Non-invasive Real-time Blood Pressure Prediction Method Based on Machine Learning","display_name":"Non-invasive Real-time Blood Pressure Prediction Method Based on Machine Learning","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2938092922","doi":"https://doi.org/10.1109/ccis.2018.8691328","mag":"2938092922"},"language":"en","primary_location":{"id":"doi:10.1109/ccis.2018.8691328","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccis.2018.8691328","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103770348","display_name":"Zhang Yongfang","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang Yongfang","raw_affiliation_strings":["Nanjing University of Posts and Telecommunications, Nanjing 210023, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Posts and Telecommunications, Nanjing 210023, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chen Xiaohui","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Xiaohui","raw_affiliation_strings":["Nanjing University of Posts and Telecommunications, Nanjing 210023, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Posts and Telecommunications, Nanjing 210023, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhang Yongsheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136219","display_name":"Kaifeng City Children's Hospital","ror":"https://ror.org/03r24h131","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210136219"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang Yongsheng","raw_affiliation_strings":["Children’s Hospital of Kaifeng City, Kaifeng 4750000, China","Children's Hospital of Kaifeng City, Kaifeng 4750000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Children’s Hospital of Kaifeng City, Kaifeng 4750000, China","institution_ids":["https://openalex.org/I4210136219"]},{"raw_affiliation_string":"Children's Hospital of Kaifeng City, Kaifeng 4750000, China","institution_ids":["https://openalex.org/I4210136219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0366,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.77103746,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"588","last_page":"592"},"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/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9707000255584717,"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/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":0.9659000039100647,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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":0.8722645044326782},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6724115014076233},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5964198112487793},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5823741555213928},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5448035001754761},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4992334842681885},{"id":"https://openalex.org/keywords/blood-pressure","display_name":"Blood pressure","score":0.48988431692123413},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46718886494636536},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4513196647167206},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.44167277216911316},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3813309371471405},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.10895141959190369},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.086171954870224},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.06997621059417725}],"concepts":[{"id":"https://openalex.org/C116390426","wikidata":"https://www.wikidata.org/wiki/Q7187885","display_name":"Photoplethysmogram","level":3,"score":0.8722645044326782},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6724115014076233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5964198112487793},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5823741555213928},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5448035001754761},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4992334842681885},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.48988431692123413},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46718886494636536},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4513196647167206},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.44167277216911316},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3813309371471405},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10895141959190369},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.086171954870224},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.06997621059417725},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccis.2018.8691328","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccis.2018.8691328","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.5400000214576721,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1656898673","https://openalex.org/W1896279358","https://openalex.org/W1977434770","https://openalex.org/W2295102988","https://openalex.org/W2341394157","https://openalex.org/W2490300818","https://openalex.org/W2516119662","https://openalex.org/W2561779441","https://openalex.org/W2580438754","https://openalex.org/W2807927092","https://openalex.org/W4376631887","https://openalex.org/W6697281604","https://openalex.org/W6853489468"],"related_works":["https://openalex.org/W2732360296","https://openalex.org/W1994871954","https://openalex.org/W4297152434","https://openalex.org/W2072858761","https://openalex.org/W1540261775","https://openalex.org/W4200107443","https://openalex.org/W4239033438","https://openalex.org/W1968279762","https://openalex.org/W4318970012","https://openalex.org/W2170552210"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,26,30,62,66,71,91,95,102,106,112,129,132,137],"accuracy":[3,139],"of":[4,7,32],"continuous":[5],"monitoring":[6],"blood":[8,39,97,118],"pressure":[9,40,98,119],"by":[10,101,140],"photoelectric":[11],"method,":[12],"and":[13,49,70,80,94],"being":[14],"unable":[15],"to":[16,29,53,75,86,110,114],"establish":[17,115],"a":[18,38,77,82],"unified":[19],"prediction":[20,41,120],"model":[21,85],"for":[22],"all":[23],"individuals":[24],"in":[25],"population":[27],"due":[28],"differences":[31],"human":[33,72],"characteristics,":[34],"this":[35],"paper":[36],"proposes":[37],"method":[42,59,134],"based":[43],"on":[44,90],"principal":[45],"component":[46],"analysis":[47],"(PCA)":[48],"genetic":[50],"algorithm":[51],"(GA)":[52],"optimize":[54,111],"machine":[55,83],"learning":[56,84],"model.":[57,121],"The":[58,122],"firstly":[60],"processes":[61],"photoplethysmography":[63],"(PPG)":[64],"signal,":[65],"electrocardiography":[67],"(ECG)":[68],"signal":[69],"body":[73],"features":[74],"form":[76],"feature":[78,92],"matrix,":[79],"uses":[81],"perform":[87],"regression":[88],"training":[89],"matrix":[93],"real-time":[96],"value":[99],"measured":[100],"mercury":[103],"sphygmomanometer.":[104],"Then,":[105],"GA":[107],"is":[108],"used":[109],"parameters":[113],"an":[116],"optimal":[117],"experimental":[123],"results":[124],"show":[125],"that":[126],"compared":[127],"with":[128],"traditional":[130],"SVR,":[131],"proposed":[133],"could":[135],"improve":[136],"predictive":[138],"10%-15%.":[141]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}