Tracking Radial Artery Dynamics Using Brightness-Mode Ultrasound and Video Analysis
: Bahmani, Nima; Kärkkäinen, Titus; Kantola, Janne; Aarela, Oula; Häkkänen, Otso; Turakainen, Venla; Panula, Tuukka; Vujaklija, Ivan; Sigg, Stephan; Nässi, Viktor; Carlson, Craig S.
: Beigl, Michael; Jacucci, Giulio; Sigg, Stephan; Xiao, Yu; Bardram, Jakob; Eleni Tsiropoulou, Eirini; Xu, Chenren
: ACM international joint conference on pervasive and ubiquitous computing
Publisher: ACM
: 2025
ACM international joint conference on pervasive and ubiquitous computing
: UbiComp Companion '25 : Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing
: 300
: 304
: 979-8-4007-1477-1
DOI: https://doi.org/10.1145/3714394.3755877
: https://dl-acm-org.ezproxy.utu.fi:2443/doi/10.1145/3714394.3755877
: https://research.utu.fi/converis/portal/detail/Publication/508524260
: ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) / ACM International Symposium on Wearable Computers (ISWC)
Cardiovascular disease is an important concern and the evaluation of vascular health is a key element for early detection. However, continuous non-invasive measurement of vascular health is limited to clinical settings while wearable health sensing devices are lacking vascular health detection. To achieve such wearable continuous cardiovascular health measurement, better understanding about physical properties of the vascular system are needed. Towards the development of wearable continuous cardiovascular health monitoring, we developed, verified, and validated an algorithm to estimate the dynamic radius of the radial artery and estimated the arterial pulsation from brightness-mode ultrasound imaging. The algorithm was implemented using Python and MATLAB®. The algorithm was tested using a simulation environment, as well as ultrasound imaging together with continuous non-invasive arterial pressure monitoring from participants. The radial artery size and distance from surface measured was >90% accurate. We report an informative summary from 6 participants. The radial artery radius change over time was used to estimate heart-beat rate, and showed reasonable accuracy for 5 out of 6 participants.
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This work was supported by the Finnish Doctoral Program Networkin Artificial Intelligence, AI-DOC (decision number VN/3137/2024-OKM-6). Authors state no conflict of interest. Informed consent hasbeen obtained from all individuals included in this study. The re-search related to human use complies with all the relevant nationalregulations, institutional policies and was performed in accordancewith the tenets of the Helsinki Declaration, and has received ap-proval from the ethics committee of Aalto University (approval IDD/10330/03.04/2024).
