Ultrasound evaluation of the radial artery in young adults — A pilot study

Domagała, Zygmunt; Grzelak, Joanna; Pospiech, Natalie; Hunter, Nicole; Klekowski, Jakub; Lach, Agnieszka; Stój, Katarzyna; Kurc-Darak, Bożena; Trzaska, Mirosław

doi:10.1016/j.aanat.2021.151763

Cited by 11 publications

(8 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The strain sensor shows the ability to detect high-quality pulse signals with a radial artery depth of up to 5 mm (fig. S9), fulfilling requirement for most users ( 69 ). In addition, for users with thick subcutaneous fat layers and radial artery depth up to 7 mm, satisfactory pulse signals can be acquired by applying an additional pressure on the skin (fig.…”

Section: Resultsmentioning

confidence: 99%

Monitoring blood pressure and cardiac function without positioning via a deep learning–assisted strain sensor array

Li,

Wang,

et al. 2023

Sci. Adv.

View full text Add to dashboard Cite

Continuous and reliable monitoring of blood pressure and cardiac function is of great importance for diagnosing and preventing cardiovascular diseases. However, existing cardiovascular monitoring approaches are bulky and costly, limiting their wide applications for early diagnosis. Here, we developed an intelligent blood pressure and cardiac function monitoring system based on a conformal and flexible strain sensor array and deep learning neural networks. The sensor has a variety of advantages, including high sensitivity, high linearity, fast response and recovery, and high isotropy. Experiments and simulation synergistically verified that the sensor array can acquire high-precise and feature-rich pulse waves from the wrist without precise positioning. By combining high-quality pulse waves with a well-trained deep learning model, we can monitor blood pressure and cardiac function parameters. As a proof of concept, we further constructed an intelligent wearable system for real-time and long-term monitoring of blood pressure and cardiac function, which may contribute to personalized health management, precise and early diagnosis, and remote treatment.

show abstract

Section: Resultsmentioning

confidence: 99%

Monitoring blood pressure and cardiac function without positioning via a deep learning–assisted strain sensor array

Li,

Wang,

et al. 2023

Sci. Adv.

View full text Add to dashboard Cite

show abstract

“…Then, the position of the cuffless BPM set in this simulator also affects the delay of the measured reflection wave. In this study, we placed the cuffless BPM at 2 cm before the tube turn, similar to placing the device at 2 cm above the styloid process when testing the wrist of a real person [ 21 ]. Figure 2 b shows the system’s aneroid gauge.…”

Section: Methodsmentioning

confidence: 99%

A Hemodynamic Pulse Wave Simulator Designed for Calibration of Local Pulse Wave Velocities Measurement for Cuffless Techniques

Guo¹,

Perng

Chen³

et al. 2023

Micromachines

View full text Add to dashboard Cite

Objective: Devices for cuffless blood pressure (BP) measurement have become increasingly widespread in recent years. Non-invasive continuous BP monitor (BPM) devices can diagnose potential hypertensive patients at an early stage; however, these cuffless BPMs require more reliable pulse wave simulation equipment and verification methods. Therefore, we propose a device to simulate human pulse wave signals that can test the accuracy of cuffless BPM devices using pulse wave velocity (PWV). Methods: We design and develop a simulator capable of simulating human pulse waves comprising an electromechanical system to simulate the circulatory system and an arm model-embedded arterial phantom. These parts form a pulse wave simulator with hemodynamic characteristics. We use a cuffless device for measuring local PWV as the device under test to measure the PWV of the pulse wave simulator. We then use a hemodynamic model to fit the cuffless BPM and pulse wave simulator results; this model can rapidly calibrate the cuffless BPM’s hemodynamic measurement performance. Results: We first used multiple linear regression (MLR) to generate a cuffless BPM calibration model and then investigated differences between the measured PWV with and without MLR model calibration. The mean absolute error of the studied cuffless BPM without the MLR model is 0.77 m/s, which improves to 0.06 m/s when using the model for calibration. The measurement error of the cuffless BPM at BPs of 100–180 mmHg is 1.7–5.99 mmHg before calibration, which decreases to 0.14–0.48 mmHg after calibration. Conclusion: This study proposes a design of a pulse wave simulator based on hemodynamic characteristics and provides a standard performance verification method for cuffless BPMs that requires only MLR modeling on the cuffless BPM and pulse wave simulator. The pulse wave simulator proposed in this study can be used to quantitively assess the performance of cuffless BPMs. The proposed pulse wave simulator is suitable for mass production for the verification of cuffless BPMs. As cuffless BPMs become increasingly widespread, this study can provide performance testing standards for cuffless devices.

show abstract

“…11, we used the L-Type ultrasound probe to measure the participant's radial artery [60]. We placed the ultrasound probe against the contact surface without pressure between 2 cm above the styloid process and 6 cm above the styloid process [61]. We reference the method of assessing radial artery in systemic disease to measure the arterial diameter and intimal thickness [62].…”

Section: A Ultrasound Imaging Of the Radial Arterymentioning

confidence: 99%

Assessment of a Calibration-Free Method of Cuffless Blood Pressure Measurement: A Pilot Study

Guo¹,

Chang²,

Wang³

et al. 2023

IEEE J. Transl. Eng. Health Med.

View full text Add to dashboard Cite

This study proposes a low-cost, high-sensitivity sensor of beat-to-beat local pulse wave velocity (PWV), to be used in a cuffless blood pressure monitor (BPM). Objective: We design an adaptive algorithm to detect the feature of the pulse wave, making it possible for two sensors to measure the local PWV in the radial artery at a short distance. Unlike the cuffless BPM that needs to use a regression model for calibration. Method: We encapsulate the piezoelectric sensor material in a cavity and design an analog front-end circuit. This study used color ultrasound imaging equipment to measure radial arterial parameters, including the diameter and wall thickness, to aid the estimation of blood pressure (BP) using the Moens-Korteweg (MK) equation of hemodynamics. Results: We compared the blood pressure estimated by the MK equation with the reference BP measured using an aneroid sphygmomanometer in a test group of 32 people, resulting in a mean difference of systolic BP of -0.63 mmHg, and a standard deviation of ±5.14 mmHg, a mean difference of mean arterial pressure (MAP) of 0.97 mmHg, with a standard deviation of ±3.54 mmHg, and a mean difference of diastolic BP of -1.14 mmHg, with a standard deviation of ±4.08 mmHg. This study has verified its compliance with ISO 81060-2. Conclusions: A new type of wearable continuous calibration-free BPM can replace the situation that requires the use of traditional ambulatory BPM and reduce patient discomfort. Clinical impact: In this study can provide long-term continuous blood pressure monitoring in the hospital.

show abstract

Ultrasound evaluation of the radial artery in young adults — A pilot study

Cited by 11 publications

References 55 publications

Monitoring blood pressure and cardiac function without positioning via a deep learning–assisted strain sensor array

Monitoring blood pressure and cardiac function without positioning via a deep learning–assisted strain sensor array

A Hemodynamic Pulse Wave Simulator Designed for Calibration of Local Pulse Wave Velocities Measurement for Cuffless Techniques

Assessment of a Calibration-Free Method of Cuffless Blood Pressure Measurement: A Pilot Study

Contact Info

Product

Resources

About