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dc.contributor.advisorSteinert, Martin
dc.contributor.advisorWisløff, Ulrik
dc.contributor.authorSteffensen, Torjus Lines
dc.date.accessioned2023-12-21T10:17:39Z
dc.date.available2023-12-21T10:17:39Z
dc.date.issued2023
dc.identifier.isbn978-82-326-7415-2
dc.identifier.issn2703-8084
dc.identifier.urihttps://hdl.handle.net/11250/3108549
dc.description.abstractEnglish summary: Cardiovascular monitoring has become ubiquitous with the advent of modern smartwatches and smartphones. We can track our heart rates and oxygen saturation through the day, as we sleep, we can record our breathing rate and how much we toss and turn. Some devices allow for detection of arrhythmia. An additional vital sign has been a high research priority. Tracking blood pressure at the same level of ease and high temporal resolution offers to revolutionize diagnosis and management of hypertension, as well as ambulatory blood pressure research. Bringing about this vision has proven difficult. Developments in sensor systems, physiological understanding, and signal processing have brought this technology to the cusp of reliability. This thesis presents seven contributions revolving around a central study of a wrist-worn wearable sensor intended to investigate novel approaches for blood pressure estimation. Supporting this study are several sub-projects contributing to technology development and problem understanding. The primary results indicate that the use of such sensors, in combination with advanced signal processing and deep learning techniques, allows for the non-invasive estimation of blood pressure and arterial stiffness even during moderate to high-intensity exercise. The additional contributions offer insights into the domain applications, further enriching their respective bodies of literature.en_US
dc.description.abstractNorsk sammendrag: Med moderne smartklokker og smarttelefoner har overvåking av hjerte- og karsystemet blitt dagligdags. Vi kan følge hjertefrekvens og oksygenmetning gjennom dagen, mens vi sover kan vi logge pustefrekvens og hvor urolige vi er. Noen enheter kan også detektere arytmier. En annen parameter har vært en høy forskningsprioritet. Overvåkning av blodtrykk med samme letthet og høye tidsoppløsning kan revolusjonere diagnose og behandling av hypertensjon så vel som ambulant blodtrykksforskning. Å realisere denne visjonen har vist seg å være vanskelig. Utviklinger innen sensorsystemer, fysiologisk forståelse og signalbehandling har brakt teknologien til randen av pålitelighet. Denne avhandlingen presenterer syv bidrag som bygger opp om en sentral studie av en bærbar sensor ment for å undersøke nye metoder for blodtrykksestimering. Støttende for denne studien er flere underprosjekter som har bidratt til teknologiutvikling og problemforståelse. Hovedresultatene indikerer at bruk av disse sensorene, i kombinasjon med avansert signalbehandling og maskinlæringsteknikker som dyp læring, muliggjør ikke-invasiv estimering av blodtrykk og arteriestivhet selv under moderat til høy intensitet trening. De ytterligere bidragene gir innsikt i respektive domeneapplikasjoner og beriker den respektive litteraturen.en_US
dc.language.isoengen_US
dc.publisherNTNUen_US
dc.relation.ispartofseriesDoctoral theses at NTNU;2023:358
dc.relation.haspartContribution 1: Gjerde, Simon Gåseby; Steffensen, Torjus Lines; Vestad, Håvard; Steinert, Martin. Windows to the Sole: Prototyping Soft Sensors for Wearable Ballistocardiography. I: International Conference on Wearable and Implantable Body Sensor Networks (IEEE BHI-BSN 2022). IEEE conference proceedings 2022 ISBN 978-1-6654-5925-9. s. - © Copyright 2022 IEEE. Available at: http://dx.doi.org/10.1109/BSN56160.2022.9928472en_US
dc.relation.haspartContribution 2: Steffensen, Torjus Lines; Auflem, Marius; Vestad, Håvard; Steinert, Martin. Embedded Soft Inductive Sensors to Measure Arterial Expansion of Tubular Diameters in Vascular Phantoms. IEEE Sensors Journal 2022 ;Volum 22.(7) s. 7240-7247. Published by IEEE. This work is licensed under a Creative Commons Attribution 4.0 License CC BY. Available at: http://dx.doi.org/10.1109/JSEN.2022.3155071en_US
dc.relation.haspartContribution 3: Steffensen, Torjus Lines; Schjerven, Filip Emil; Flade, Hans Martin; Kirkeby-Garstad, Idar; Ingeström, Emma Maria Lovisa; Solberg, Fredrik Samdal; Steinert, Martin. Wrist ballistocardiography and invasively recorded blood pressure in healthy volunteers during reclining bike exercise. Frontiers in Physiology 2023 ;Volum 14. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). Available at: http://dx.doi.org/10.3389/fphys.2023.1189732en_US
dc.relation.haspartContribution 4: Steffensen, Torjus Lines; Schjerven, Filip Emil; Flade, Hans Martin; Kirkeby-Garstad, Idar; Ingeström, Emma Maria Lovisa; Solberg, Fredrik Samdal; Steinert, Martin. Cuffless estimation of continuous blood pressure during recumbent bike exercise: comparison of wearable tonometry and PPG against invasive ground-truth measurements. This paper is awaiting publication and is therefore not included.en_US
dc.relation.haspartContribution 5: Steffensen, Torjus Lines; Kriesi, Carlo; Steinert, Martin; Lafrenz, Thomas; Brede, Jostein; Auflem, Marius. Ultrasound phantom. US patent pending. This is a pending patent and is not included.en_US
dc.relation.haspartContribution 6: Steffensen, Torjus Lines; Kohtala, Sampsa Matias Ilmari; Vestad, Håvard Nitter; Steinert, Ralf Martin. TrollBOT: A Spontaneous Networking Tool Facilitating Rapid Prototyping of Wirelessly Communicating Products. Procedia CIRP 2020 ;Volum 91. s. 634-638. Published by Elsevier. This is an open access article under the CC BY-NC-ND license. Available at: http://dx.doi.org/10.1016/j.procir.2020.03.111en_US
dc.titleVitals on the wrist Sensor development for unobtrusive and ubiquitous cardiovascular monitoringen_US
dc.typeDoctoral thesisen_US
dc.subject.nsiVDP::Medisinske Fag: 700en_US


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