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基于人工智能的单耳贴片光容积脉搏波在心肺复苏期间的动脉血压估计。

Estimation of Arterial Blood Pressure Based on Artificial Intelligence Using Single Earlobe Photoplethysmography during Cardiopulmonary Resuscitation.

机构信息

Department of Biomedical Engineering, College of Health Science, Yonsei University, Wonju, Kangwon-do, 26493, South Korea.

R&D Center, MEDIANA Co., Ltd., Wonju, Republic of Korea.

出版信息

J Med Syst. 2019 Dec 10;44(1):18. doi: 10.1007/s10916-019-1514-z.

DOI:10.1007/s10916-019-1514-z
PMID:31823091
Abstract

This study investigates the feasibility of estimation of blood pressure (BP) using a single earlobe photoplethysmography (Ear PPG) during cardiopulmonary resuscitation (CPR). We have designed a system that carries out Ear PPG for estimation of BP. In particular, the BP signals are estimated according to a long short-term memory (LSTM) model using an Ear PPG. To investigate the proposed method, two statistical analyses were conducted for comparison between BP measured by the micromanometer-based gold standard method (BP) and the Ear PPG-based proposed method (BP) for swine cardiac model. First, Pearson's correlation analysis showed high positive correlations (r = 0.92, p < 0.01) between BP and BP. Second, the paired-samples t-test on the BP parameters (systolic and diastolic blood pressure) of the two methods indicated no significant differences (p > 0.05). Therefore, the proposed method has the potential for estimation of BP for CPR biofeedback based on LSTM using a single Ear PPG.

摘要

本研究旨在探讨在心肺复苏(CPR)期间使用单个耳垂光体积描记法(Ear PPG)估计血压(BP)的可行性。我们设计了一种系统,该系统可进行 Ear PPG 以估计 BP。具体来说,根据长短期记忆(LSTM)模型使用 Ear PPG 来估计 BP 信号。为了研究该方法,针对猪心脏模型,我们对基于微动脉血压计的金标准方法(BP)和基于 Ear PPG 的提出方法(BP)测量的 BP 进行了两项统计学分析。首先,Pearson 相关分析显示 BP 和 BP 之间存在高度正相关(r=0.92,p<0.01)。其次,两种方法的 BP 参数(收缩压和舒张压)的配对样本 t 检验表明无显著差异(p>0.05)。因此,该方法有可能基于 LSTM 使用单个 Ear PPG 进行 CPR 生物反馈的 BP 估计。

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本文引用的文献

1
Transthoracic Impedance Measured with Defibrillator Pads-New Interpretations of Signal Change Induced by Ventilations.使用除颤器电极片测量经胸阻抗——通气引起的信号变化的新解释
J Clin Med. 2019 May 22;8(5):724. doi: 10.3390/jcm8050724.
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Arterial blood pressure feature estimation using photoplethysmography.基于光电容积脉搏波的动脉血压特征估计。
Comput Biol Med. 2018 Nov 1;102:104-111. doi: 10.1016/j.compbiomed.2018.09.013. Epub 2018 Sep 19.
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Detection of spontaneous pulse using the acceleration signals acquired from CPR feedback sensor in a porcine model of cardiac arrest.
基于深度学习的非接触式 IPPG 信号血压测量研究。
Sensors (Basel). 2023 Jun 13;23(12):5528. doi: 10.3390/s23125528.
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Biomed Opt Express. 2021 Nov 19;12(12):7732-7751. doi: 10.1364/BOE.444535. eCollection 2021 Dec 1.
在猪心脏骤停模型中,利用从心肺复苏反馈传感器获取的加速度信号检测自发脉搏。
PLoS One. 2017 Dec 8;12(12):e0189217. doi: 10.1371/journal.pone.0189217. eCollection 2017.
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Part 4: Advanced Life Support: 2015 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations.第4部分:高级生命支持:2015年国际心肺复苏和心血管急救科学与治疗建议共识。
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Improving cardiopulmonary resuscitation with a CPR feedback device and refresher simulations (CPR CARES Study): a randomized clinical trial.使用心肺复苏反馈装置和复苏模拟训练改进心肺复苏(CPR CARES 研究):一项随机临床试验。
JAMA Pediatr. 2015 Feb;169(2):137-44. doi: 10.1001/jamapediatrics.2014.2616.
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Intracranial pressure following cardiopulmonary resuscitation.心肺复苏后的颅内压
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