胸阻抗信号监测心肺复苏质量的方法研究
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摘要
心脏骤停（cardiac arrest, CA），又称心源性猝死（sudden cardiac death，SCD）是指心脏的机械活动停止，同时左心室收缩不足或停止收缩。心脏骤停80%以上都发生在院外，又称院外心脏骤停（Out-of-hospital cardiac arrest，OHCA)。据统计，在美国每年约有33万人发生OHCA，在欧洲每年约有35万人，而在中国这一数字则高达55.4万人。
心肺复苏（cardiopulmonary resuscitation，CPR）作为全球医学界研究的热点之一，是抢救心脏骤停患者的唯一有效途径。CPR包括胸外按压、人工通气和体外电除颤等。美国心脏协会（American heart association, AHA）在2010年复苏指南中进一步强调，及早进行高质量的胸外按压是提高CPR成功率的关键措施。
胸外按压（chest compression，CC）的质量包括按压深度、按压频率和胸廓的回弹程度等。尤其是足够的按压深度，它是保持一定冠状动脉灌注压（coronary perfusionpressure, CPP）的关键。CPP被证实是目前预测能否恢复自主循环（return of spontaneouscirculation，ROSC）的最直接的指标。但是，研究表明许多心脏骤停患者在CPR过程中没有得到有效的胸外按压，主要表现在按压深度不足、按压频率较低以及没有保持适当的循环血流。由于OHCA病人的第一目击者绝大多数是非专业人员，使得院外CPR的质量更加得不到保障，调查显示目前全球总体CPR成功率不到10%。
目前监测心肺复苏质量的手段主要有监测CPR实施过程的CPP、按压深度、按压频率等参数。CPP能很好预测心肺复苏成功率，但是由于它需要进行有创监测而无法得到广泛应用。按压深度和频率可以通过在患者胸口上方放置加速度传感器或位移传感器来获得，但需要额外增加器件是它存在的固有缺陷。尽管经胸阻抗（Transthoracicimpedance，TTI）在心肺复苏领域应用广泛，但利用TTI实时监测胸外按压质量的研究仍未见报道，且目前尚未建立TTI变化与CPP和按压深度之间的关系。如何利用TTI信号对心肺复苏质量进行监测并实时反馈，是一项具有重要意义的研究课题。
针对上述问题，本论文对以下两个方面内容开展了研究：
1.建立动物实验模型并研究TTI变化值与CPP和按压深度之间的关系。我们通过实验建立了家猪心跳骤停（6分钟室颤）与不同人工心肺复苏质量模型，并通过高质量按压组和低质量按压组进行对照研究。在本实验中，高质量按压组的按压深度不低于胸部前后径幅度的25%（即50mm），低质量按压组的按压深度为高质量按压组的70%（即35mm）。实验结果显示，高质量按压组所有动物均获得ROSC，低质量按压组仅2头动物获得ROSC（100%vs.28.57%, p=0.021）。TTI变化值和按压深度的相关系数为0.89（P<0.001），TTI变化值和CPP的相关系数为0.83（P<0.001），均具有很好的线性相关性。
2.利用TTI信号监测心肺复苏质量并进行实时反馈。为准确获取TTI信号中包含的TTI变化值、按压频率、按压通气比、按压时间比等反映心肺复苏质量的指标并进行实时反馈，我们设计了基于TTI信号的检测算法。算法主要包括三个部分：（1）通过极值搜索法来检测胸外按压和人工通气的波形，并去除干扰信号。（2）通过特征提取和线性判别式分类，将检测到的信号分为按压波和通气波。（3）计算阻抗变化值、按压频率、按压通气比、按压时间比等参数，评价心肺复苏质量，通过实时显示和反馈以更好地指导救援。
我们通过心肺复苏模型的建立，研究并证实了TTI变化值与CPP和按压深度具有显著的正相关性。同时，利用基于TTI信号的检测算法，准确计算出评价心肺复苏质量参数并实时显示，对于指导心肺复苏具有重要意义。由于TTI信号可以通过除颤器的除颤电极来获取，所以不需要额外增加电子器件。因此，基于TTI信号监测心肺复苏质量的方法在心肺复苏领域具有广阔的应用前景。
Cardiac arrest（CA）,which also be called sudden cardiac death (CSD)，is a medicalemergency with absent or inadequate contraction of the left ventricle of the heart thatimmediately causes body wide circulatory failure. More than80%cardiac arrests haveoccurred out of the hospital, which also is called out-of-hospital cardiac arrest (OHCA).According to statistics, an estimated330,000victims in USA,350,000in Europe and544,000in China experience OHCA each year.
Cardiopulmonary resuscitation (CPR), which has been a focus research in the field ofmedicine all over the world, is the only effective methods to rescue the patients whoexperience CA. CPR consist of chest compression, ventilation and electrical shock and soon. The2010guidelines, therefore, emphasized the importance of performing optimal chestcompression.
The quality of chest compressions including adequate depth, frequency and full chestrecoil between compressions. Adequate depth, in particular, is the key to keeping certaincoronary perfusion pressure (CPP). CPP has been proved to be the most direct indicator toforecast the return of spontaneous circulation (ROSC). However, studies have shown thatmany patients experience CA have not get effective chest compression during CPR, mainlyshowing the lack of compression depth, low frequency and inadequate blood flow to thecirculatory system. A large quantity of investigations has confirmed that immediate andeffective CPR initiated by layperson can dramatically improve survival rate of OHCAvictims. It is report that the overall success rate of CPR is lower than10%.
The current method for monitoring the quality of chest CPR includes CPP,compression depth and frequency during CPR. CPP is a highly predictive indicator of thelikelihood of ROSC, yet it is an invasive measurement and its application is restricted. Compression depth and frequency can be obtained by placing acceleration sensors ordisplacement sensors above the chest of patients, but this method require additional sensorsand devices. Although transthoracic impedance (TTI) has been widely applied during CPR,the research that TTI for monitoring the quality of chest compressions and giving real-timedisplay has not been reported. And then, the relationship between TTI changes, CPP andcompression depth has not been established. Thus, it is a significant research topic that howto make use of the TTI signal to evaluate the quality of CPR and give a real-time feedback.
According to the above problems, in this thesis, the following two aspects of contentswere studied:
1. Building an animal experimental model and studying the relationship between TTIchanges, CPP and compression depth. In this porcine model, CA (6minutes VF) anddifferent quality of CPR model were established. Contrast study was carried out betweenhigh quality and low quality groups. Optimal depth of manual compression in high qualitygroup was defined as a decrease of25%(50mm) in anterior posterior diameter of the chest,while suboptimal compression was defined as70%of the optimal depth (35mm). Allanimals had ROSC after optimal compressions; this contrasted with suboptimalcompressions, after which only2of the animals had ROSC (100%vs.28.57%, p=0.021).The correlation coefficient was0.89between TTI amplitude and compression depth (p <0.001),0.83between TTI amplitude and CPP (p <0.001).
2. Monitoring the quality of CPR via TTI signal and giving a real-time feedback. Toaccurately get the indexes, such as TTI changes, compression frequency, compression/ventilation ratio, chest compression fraction etc, we have designed a detection algorithmbased on TTI signal, which is mainly consist of three parts:(1) detecting the peaks andtroughs of the TTI signals through the extremum search method, and then removing falsedetection.(2) Dividing the detected signal into ventilation waves and compression wavesthrough feature extraction and automatic classification.(3)Calculating the parameters suchas TTI changes, compression frequency, compression/ventilation ratio, compressionfraction to evaluate the quality of CPR and giving a real-time feedback to the rescuer.
In thesis, through the establishment of CPR model, we have studied and confirmed thatthere are significant positive correlation between the TTI changes, CPP and thecompression depth. And it has shown important meaning for guiding CPR by using TTI signals for evaluating and monitoring the quality of CPR. Because the TTI signal can beobtained from the defibrillation electrodes, there are no additional electronic devices areneeded. Therefore, the method which based on TTI for monitoring the quality of CPR andgiving a real-time feedback has a broad application prospect during CPR.
心肺复苏（cardiopulmonary resuscitation，CPR）作为全球医学界研究的热点之一，是抢救心脏骤停患者的唯一有效途径。CPR包括胸外按压、人工通气和体外电除颤等。美国心脏协会（American heart association, AHA）在2010年复苏指南中进一步强调，及早进行高质量的胸外按压是提高CPR成功率的关键措施。
胸外按压（chest compression，CC）的质量包括按压深度、按压频率和胸廓的回弹程度等。尤其是足够的按压深度，它是保持一定冠状动脉灌注压（coronary perfusionpressure, CPP）的关键。CPP被证实是目前预测能否恢复自主循环（return of spontaneouscirculation，ROSC）的最直接的指标。但是，研究表明许多心脏骤停患者在CPR过程中没有得到有效的胸外按压，主要表现在按压深度不足、按压频率较低以及没有保持适当的循环血流。由于OHCA病人的第一目击者绝大多数是非专业人员，使得院外CPR的质量更加得不到保障，调查显示目前全球总体CPR成功率不到10%。
目前监测心肺复苏质量的手段主要有监测CPR实施过程的CPP、按压深度、按压频率等参数。CPP能很好预测心肺复苏成功率，但是由于它需要进行有创监测而无法得到广泛应用。按压深度和频率可以通过在患者胸口上方放置加速度传感器或位移传感器来获得，但需要额外增加器件是它存在的固有缺陷。尽管经胸阻抗（Transthoracicimpedance，TTI）在心肺复苏领域应用广泛，但利用TTI实时监测胸外按压质量的研究仍未见报道，且目前尚未建立TTI变化与CPP和按压深度之间的关系。如何利用TTI信号对心肺复苏质量进行监测并实时反馈，是一项具有重要意义的研究课题。
针对上述问题，本论文对以下两个方面内容开展了研究：
1.建立动物实验模型并研究TTI变化值与CPP和按压深度之间的关系。我们通过实验建立了家猪心跳骤停（6分钟室颤）与不同人工心肺复苏质量模型，并通过高质量按压组和低质量按压组进行对照研究。在本实验中，高质量按压组的按压深度不低于胸部前后径幅度的25%（即50mm），低质量按压组的按压深度为高质量按压组的70%（即35mm）。实验结果显示，高质量按压组所有动物均获得ROSC，低质量按压组仅2头动物获得ROSC（100%vs.28.57%, p=0.021）。TTI变化值和按压深度的相关系数为0.89（P<0.001），TTI变化值和CPP的相关系数为0.83（P<0.001），均具有很好的线性相关性。
2.利用TTI信号监测心肺复苏质量并进行实时反馈。为准确获取TTI信号中包含的TTI变化值、按压频率、按压通气比、按压时间比等反映心肺复苏质量的指标并进行实时反馈，我们设计了基于TTI信号的检测算法。算法主要包括三个部分：（1）通过极值搜索法来检测胸外按压和人工通气的波形，并去除干扰信号。（2）通过特征提取和线性判别式分类，将检测到的信号分为按压波和通气波。（3）计算阻抗变化值、按压频率、按压通气比、按压时间比等参数，评价心肺复苏质量，通过实时显示和反馈以更好地指导救援。
我们通过心肺复苏模型的建立，研究并证实了TTI变化值与CPP和按压深度具有显著的正相关性。同时，利用基于TTI信号的检测算法，准确计算出评价心肺复苏质量参数并实时显示，对于指导心肺复苏具有重要意义。由于TTI信号可以通过除颤器的除颤电极来获取，所以不需要额外增加电子器件。因此，基于TTI信号监测心肺复苏质量的方法在心肺复苏领域具有广阔的应用前景。
Cardiac arrest（CA）,which also be called sudden cardiac death (CSD)，is a medicalemergency with absent or inadequate contraction of the left ventricle of the heart thatimmediately causes body wide circulatory failure. More than80%cardiac arrests haveoccurred out of the hospital, which also is called out-of-hospital cardiac arrest (OHCA).According to statistics, an estimated330,000victims in USA,350,000in Europe and544,000in China experience OHCA each year.
Cardiopulmonary resuscitation (CPR), which has been a focus research in the field ofmedicine all over the world, is the only effective methods to rescue the patients whoexperience CA. CPR consist of chest compression, ventilation and electrical shock and soon. The2010guidelines, therefore, emphasized the importance of performing optimal chestcompression.
The quality of chest compressions including adequate depth, frequency and full chestrecoil between compressions. Adequate depth, in particular, is the key to keeping certaincoronary perfusion pressure (CPP). CPP has been proved to be the most direct indicator toforecast the return of spontaneous circulation (ROSC). However, studies have shown thatmany patients experience CA have not get effective chest compression during CPR, mainlyshowing the lack of compression depth, low frequency and inadequate blood flow to thecirculatory system. A large quantity of investigations has confirmed that immediate andeffective CPR initiated by layperson can dramatically improve survival rate of OHCAvictims. It is report that the overall success rate of CPR is lower than10%.
The current method for monitoring the quality of chest CPR includes CPP,compression depth and frequency during CPR. CPP is a highly predictive indicator of thelikelihood of ROSC, yet it is an invasive measurement and its application is restricted. Compression depth and frequency can be obtained by placing acceleration sensors ordisplacement sensors above the chest of patients, but this method require additional sensorsand devices. Although transthoracic impedance (TTI) has been widely applied during CPR,the research that TTI for monitoring the quality of chest compressions and giving real-timedisplay has not been reported. And then, the relationship between TTI changes, CPP andcompression depth has not been established. Thus, it is a significant research topic that howto make use of the TTI signal to evaluate the quality of CPR and give a real-time feedback.
According to the above problems, in this thesis, the following two aspects of contentswere studied:
1. Building an animal experimental model and studying the relationship between TTIchanges, CPP and compression depth. In this porcine model, CA (6minutes VF) anddifferent quality of CPR model were established. Contrast study was carried out betweenhigh quality and low quality groups. Optimal depth of manual compression in high qualitygroup was defined as a decrease of25%(50mm) in anterior posterior diameter of the chest,while suboptimal compression was defined as70%of the optimal depth (35mm). Allanimals had ROSC after optimal compressions; this contrasted with suboptimalcompressions, after which only2of the animals had ROSC (100%vs.28.57%, p=0.021).The correlation coefficient was0.89between TTI amplitude and compression depth (p <0.001),0.83between TTI amplitude and CPP (p <0.001).
2. Monitoring the quality of CPR via TTI signal and giving a real-time feedback. Toaccurately get the indexes, such as TTI changes, compression frequency, compression/ventilation ratio, chest compression fraction etc, we have designed a detection algorithmbased on TTI signal, which is mainly consist of three parts:(1) detecting the peaks andtroughs of the TTI signals through the extremum search method, and then removing falsedetection.(2) Dividing the detected signal into ventilation waves and compression wavesthrough feature extraction and automatic classification.(3)Calculating the parameters suchas TTI changes, compression frequency, compression/ventilation ratio, compressionfraction to evaluate the quality of CPR and giving a real-time feedback to the rescuer.
In thesis, through the establishment of CPR model, we have studied and confirmed thatthere are significant positive correlation between the TTI changes, CPP and thecompression depth. And it has shown important meaning for guiding CPR by using TTI signals for evaluating and monitoring the quality of CPR. Because the TTI signal can beobtained from the defibrillation electrodes, there are no additional electronic devices areneeded. Therefore, the method which based on TTI for monitoring the quality of CPR andgiving a real-time feedback has a broad application prospect during CPR.
引文
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