ArticleMicromachines2022
An Arterial Compliance Sensor for Cuffless Blood Pressure Estimation Based on Piezoelectric and Optical Signals.
Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- From Cuffs to Code: Machine Learning in Non-Invasive Blood Pressure Monitoring.Anaesthesia, critical care & pain medicine · 2026Review
- Photoplethysmography acceleration indices as digital biomarkers of cardiometabolic health.Frontiers in digital health · 2026Article
- Cuffless Blood Pressure Monitor for Home and Hospital Use.Sensors (Basel, Switzerland) · 2025Review
- Emerging technologies in the field of medicine presented at the Consumer Electronics Show 2025.Journal of Yeungnam medical science · 2025Article
- On the similarity between aortic and carotid pressure diastolic decay: a mathematical modelling study.Scientific reports · 2023Article
- A Hemodynamic Pulse Wave Simulator Designed for Calibration of Local Pulse Wave Velocities Measurement for Cuffless Techniques.Micromachines · 2023Article
- A Novel Cuffless Blood Pressure Prediction: Uncovering New Features and New Hybrid ML Models.Diagnostics (Basel, Switzerland) · 2023Article
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Authors and funding
4 authors at 1 institution.
Funding
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Abstract
objectiveBlood pressure (BP) data can influence therapeutic decisions for some patients, while non-invasive devices that continuously monitor BP can provide patients with a more comprehensive BP assessment. Therefore, this study proposes a multi-sensor-based small cuffless BP monitoring device that integrates a piezoelectric sensor array and an optical sensor, which can monitor the patient's physiological signals from the radial artery.
methodBased on the Moens-Korteweg (MK) equation of the hemodynamic model, pulse wave velocity (PWV) can be correlated with arterial compliance and BP can be estimated. Therefore, the novel method proposed in this study involves using a piezoelectric sensor array to measure the PWV and an optical sensor to measure the photoplethysmography (PPG) intensity ratio (PIR) signal to estimate the participant's arterial parameters. The parameters measured by multiple sensors were combined to estimate BP based on the P-β model derived from the MK equation.
resultWe recruited 20 participants for the BP monitoring experiment to compare the performance of the BP estimation method with the regression model and the P-β model method with arterial compliance. We then compared the estimated BP with a reference device for validation. The results are presented as the error mean ± standard deviation (SD). Based on the regression model method, systolic blood pressure (SBP) was 0.32 ± 5.94, diastolic blood pressure (DBP) was 2.17 ± 6.22, and mean arterial pressure (MAP) was 1.55 ± 5.83. The results of the P-β model method were as follows: SBP was 0.75 ± 3.9, DBP was 1.1 ± 3.12, and MAP was 0.49 ± 2.82.
conclusionAccording to the results of our proposed small cuffless BP monitoring device, both methods of estimating BP conform to ANSI/AAMI/ISO 81060-2:20181_5.2.4.1.2 criterion 1 and 2, and using arterial parameters to calibrate the MK equation model can improve BP estimate accuracy. In the future, our proposed device can provide patients with a convenient and comfortable BP monitoring solution. Since the device is small, it can be used in a public place without attracting other people's attention, thereby effectively improving the patient's right to privacy, and increasing their willingness to use it.
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