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Radial pulse rate estimation from brightness-mode ultrasound imaging
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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en
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4
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Current Directions in Biomedical Engineering, Volume 11, issue 1, pp. 286-289
Abstract
Cardiovascular disease is a global concern with a high economic burden that needs to be controlled. Predictors of cardiovascular disease include blood pressure. There is a drive to evaluate these predictors through continuous non-invasive methods, which often requires custom devices to achieve the measurements. To reduce reliance on custom devices, we developed, verified, and validated an algorithm to measure the dynamic cross-sectional area of the radial artery and estimate the pulse rate from brightness-mode ultrasound imaging. The algorithm was implemented using Python and MATLAB®, and verified using a simulated environment with known parameters. It was validated using radial artery ultrasound scans, where pulse rate estimation was confirmed using continuous non-invasive arterial pressure monitoring as the control. The algorithm was verified to measure the area at >99 % accuracy with a difference in pixel value between artery and background >20 when considering a complex signal. The pulse rate estimate was exact. The accuracy of area measurement decreased when applied to ultrasound scans. However, the algorithm still estimated the pulse rate within the error margin, compared to the control, for five out of six subjects thus validating the algorithm. This demonstrates the possibility of measuring physiological factors without the need of custom devices. With further development, this algorithm could incorporate colour doppler information such that arterial pressure could be determined using a medical ultrasound device.
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Bahmani, N, Kärkkäinen, T, Kantola, J, Aarela, O, Häkkänen, O, Turakainen, V, Nässi, V, Panula, T, Vujaklija, I, Sigg, S & Carlson, C S 2025, 'Radial pulse rate estimation from brightness-mode ultrasound imaging', Current Directions in Biomedical Engineering, vol. 11, no. 1, pp. 286-289. https://doi.org/10.1515/cdbme-2025-0173