Design and Implementation of a Non-invasive and Cuff-less Arterial Blood Pressure Monitoring System

dc.contributor.authorSeyed Mohsen Anvari
dc.contributor.authorMohammadreza Yazdchi
dc.contributor.authorAmirhossein Kayvanpour
dc.contributor.authorSeyed Mohammad Hasan Nayebpour
dc.contributor.authorTero Koivisto
dc.contributor.authorMojtaba Jafari Tadi
dc.contributor.organizationfi=biolääketieteen laitos|en=Institute of Biomedicine|
dc.contributor.organizationfi=kieli- ja puheteknologia|en=Language and Speech Technology|
dc.contributor.organizationfi=tyks, vsshp|en=tyks, varha|
dc.contributor.organization-code1.2.246.10.2458963.20.47465613983
dc.contributor.organization-code1.2.246.10.2458963.20.77952289591
dc.converis.publication-id28771555
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/28771555
dc.date.accessioned2022-10-27T11:50:48Z
dc.date.available2022-10-27T11:50:48Z
dc.description.abstract<p> </p><div> <div> <div> <p>Hypertension or high blood pressure (BP) is one of the most common worldwide disease leading to heart attack or stroke. Continuous assessment of blood pressure level is key to diagnosing hypertension. In this study, we de- signed and tested a dedicated cuff-less monitoring system which estimates BP level without need for calibration. We obtained continuous measurements from 40 healthy sub- jects (30 males and 10 females) ranging from 20-30 years old. Our measurement protocol consisted of 15 minutes si- multaneous electrocardiography (ECG) and photoplethys- mography (PPG) within three sessions, i.e. rest, bicycle exercise, and recovery. From ECG and PPG signals, we obtained 34 candidate features from which up to 9 features were selected to estimate systolic and diastolic BP levels. We validate our results with three regression models such as linear regression, support vector machines (SVM) re- gression, and multilayer perceptron (MLP) to obtain the best results. The study provides a promising approach for modern cuff-less BP monitoring devices. </p> </div> </div> </div>
dc.identifier.issn2325-8861
dc.identifier.jour-issn2325-8861
dc.identifier.olddbid172245
dc.identifier.oldhandle10024/155339
dc.identifier.urihttps://www.utupub.fi/handle/11111/29970
dc.identifier.urlhttp://www.cinc.org/archives/2017/pdf/325-471.pdf
dc.identifier.urnURN:NBN:fi-fe2021042718148
dc.language.isoen
dc.okm.affiliatedauthorKoivisto, Tero
dc.okm.affiliatedauthorJafari Tadi, Mojtaba
dc.okm.affiliatedauthorDataimport, tyks, vsshp
dc.okm.discipline217 Medical engineeringen_GB
dc.okm.discipline3141 Health care scienceen_GB
dc.okm.discipline217 Lääketieteen tekniikkafi_FI
dc.okm.discipline3141 Terveystiedefi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA4 Conference Article
dc.publisher.countryUnited Statesen_GB
dc.publisher.countryYhdysvallat (USA)fi_FI
dc.publisher.country-codeUS
dc.relation.conferenceComputing in Cardiology
dc.relation.doi10.22489/CinC.2017.325-471
dc.relation.ispartofjournalComputing in Cardiology
dc.relation.volume44
dc.source.identifierhttps://www.utupub.fi/handle/10024/155339
dc.titleDesign and Implementation of a Non-invasive and Cuff-less Arterial Blood Pressure Monitoring System
dc.title.bookComputing in Cardiology
dc.year.issued2017

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