Feasibility of waveform separation of central aortic pressure pulse based on lognormal flow wave approximation

Hao, Liling; Zhang, Qi; Chen, Xuewei; Yao, Yu-Dong; Xu, Lisong

doi:10.1016/j.bspc.2022.103784

Cited by 5 publications

(4 citation statements)

References 35 publications

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“…Typically, some degree of flow regurgitation occurs when the aortic valve closes, i.e., the actual aortic flow is negative at end-systole (shown in Figure 8). As with the triangular and the lognormal flow waves, the proposed personalized flow wave ignores this by setting the diastolic flow to 0 (Westerhof et al, 2006;Hao et al, 2022). Although the personalized flow wave improves the results of wave reflection and wave separation analysis compared to the other two methods, it is still necessary to further strengthen this research to implement this typical feature of aortic flow waveform.…”

Section: Discussionmentioning

confidence: 99%

“…As with the triangular flow waveform, there is a specific relationship between the characteristic points of the lognormal flow waveform and the characteristic points of CAPW. As shown in Figure 6B, the start, peak, and end points of the lognormal flow waveform correspond to the foot, the inflection point, and the dicrotic notch point of the CAPW, respectively (Plamondon et al, 2013;Hao et al, 2022).…”

Section: Triangular and Lognormal Flow Waveformmentioning

confidence: 99%

“…The sample set included only 49 young (18-42 years) and 29 older (51-77 years) adults. More recently, a novel lognormal flow wave method for separating the CAPW was proposed by Hao et al (Hao et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Wave reflection quantification analysis and personalized flow wave estimation based on the central aortic pressure waveform

Sun

Yang²,

Liu³

et al. 2023

Front. Physiol.

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Pulse wave reflections reflect cardiac afterload and perfusion, which yield valid indicators for monitoring cardiovascular status. Accurate quantification of pressure wave reflections requires the measurement of aortic flow wave. However, direct flow measurement involves extra equipment and well-trained operator. In this study, the personalized aortic flow waveform was estimated from the individual central aortic pressure waveform (CAPW) based on pressure-flow relations. The separated forward and backward pressure waves were used to calculate wave reflection indices such as reflection index (RI) and reflection magnitude (RM), as well as the central aortic pulse transit time (PTT). The effectiveness and feasibility of the method were validated by a set of clinical data (13 participants) and the Nektar1D Pulse Wave Database (4,374 subjects). The performance of the proposed personalized flow waveform method was compared with the traditional triangular flow waveform method and the recently proposed lognormal flow waveform method by statistical analyses. Results show that the root mean square error calculated by the personalized flow waveform approach is smaller than that of the typical triangular and lognormal flow methods, and the correlation coefficient with the measured flow waveform is higher. The estimated personalized flow waveform based on the characteristics of the CAPW can estimate wave reflection indices more accurately than the other two methods. The proposed personalized flow waveform method can be potentially used as a convenient alternative for the measurement of aortic flow waveform.

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Section: Discussionmentioning

confidence: 99%

Section: Triangular and Lognormal Flow Waveformmentioning

confidence: 99%

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Wave reflection quantification analysis and personalized flow wave estimation based on the central aortic pressure waveform

Sun

Yang²,

Liu³

et al. 2023

Front. Physiol.

Self Cite

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“…The tube’s properties will affect the backward wave’s reflection delay, such as length, diameter, and wall thickness [ 18 , 19 ]. Moreover, since arterial bifurcation, plaques, and terminal arterioles will affect the reflected wave, the reaction force generates a wave [ 20 ]. This wave will move backward (or centrifugally) with the same velocity, and the transverse displacement of the centripetal wave is reversed or 180°.…”

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

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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.

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Pulse wave signal modelling and feature extraction based on Lognormal function from photoplethysmography in wireless body area networks

Gao

2023

Biomedical Signal Processing and Control

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Feasibility of waveform separation of central aortic pressure pulse based on lognormal flow wave approximation

Cited by 5 publications

References 35 publications

Wave reflection quantification analysis and personalized flow wave estimation based on the central aortic pressure waveform

Wave reflection quantification analysis and personalized flow wave estimation based on the central aortic pressure waveform

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

Pulse wave signal modelling and feature extraction based on Lognormal function from photoplethysmography in wireless body area networks

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