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一种评估血压波形的无创方法综述。

A Review of Noninvasive Methodologies to Estimate the Blood Pressure Waveform.

机构信息

School of Electrical Engineering, Kookmin University, Seoul 02707, Korea.

出版信息

Sensors (Basel). 2022 May 23;22(10):3953. doi: 10.3390/s22103953.

DOI:10.3390/s22103953
PMID:35632360
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9145242/
Abstract

Accurate estimation of blood pressure (BP) waveforms is critical for ensuring the safety and proper care of patients in intensive care units (ICUs) and for intraoperative hemodynamic monitoring. Normal cuff-based BP measurements can only provide systolic blood pressure (SBP) and diastolic blood pressure (DBP). Alternatively, the BP waveform can be used to estimate a variety of other physiological parameters and provides additional information about the patient's health. As a result, various techniques are being proposed for accurately estimating the BP waveforms. The purpose of this review is to summarize the current state of knowledge regarding the BP waveform, three methodologies (pressure-based, ultrasound-based, and deep-learning-based) used in noninvasive BP waveform estimation research and the feasibility of employing these strategies at home as well as in ICUs. Additionally, this article will discuss the physical concepts underlying both invasive and noninvasive BP waveform measurements. We will review historical BP waveform measurements, standard clinical procedures, and more recent innovations in noninvasive BP waveform monitoring. Although the technique has not been validated, it is expected that precise, noninvasive BP waveform estimation will be available in the near future due to its enormous potential.

摘要

准确估计血压 (BP) 波形对于确保重症监护病房 (ICU) 中患者的安全和适当护理以及术中血流动力学监测至关重要。传统的袖带式血压测量方法只能提供收缩压 (SBP) 和舒张压 (DBP)。而血压波形则可以用于估计各种其他生理参数,并提供有关患者健康状况的额外信息。因此,人们提出了各种技术来准确估计血压波形。本综述的目的是总结当前关于血压波形的知识状态,以及在非侵入性血压波形估计研究中使用的三种方法(基于压力的、基于超声的和基于深度学习的),以及在家庭和 ICU 中应用这些策略的可行性。此外,本文还将讨论基于有创和非有创血压波形测量的物理概念。我们将回顾历史上的血压波形测量、标准临床程序以及非侵入性血压波形监测的最新创新。尽管该技术尚未得到验证,但由于其巨大的潜力,预计在不久的将来将能够实现精确的、非侵入性的血压波形估计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ce4/9145242/93743fbffef6/sensors-22-03953-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ce4/9145242/17b570880607/sensors-22-03953-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ce4/9145242/d799c94bc8ee/sensors-22-03953-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ce4/9145242/2fcd48296ce9/sensors-22-03953-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ce4/9145242/ce354f3fc99e/sensors-22-03953-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ce4/9145242/93743fbffef6/sensors-22-03953-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ce4/9145242/17b570880607/sensors-22-03953-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ce4/9145242/d799c94bc8ee/sensors-22-03953-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ce4/9145242/2fcd48296ce9/sensors-22-03953-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ce4/9145242/ce354f3fc99e/sensors-22-03953-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ce4/9145242/04edecdddbad/sensors-22-03953-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ce4/9145242/93743fbffef6/sensors-22-03953-g006.jpg

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