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Towards virtual instruments for cardiovascular healthcare: Real-time modeling of cardiovascular dynamics using ECG signals

机译:迈向用于心血管保健的虚拟仪器:使用ECG信号对心血管动力学进行实时建模

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As cardiovascular disorders have emerged as the primary cause of human mortality, quantitative modeling of cardiovascular system, including the dynamic coupling among its chemical, electrical and pulmonary mechanisms, has evoked keen interest in the recent years. The current dynamic models have little clinical relevance because they cannot be correlated with the real-time signals from a human heart. This research presents a new approach for real-time simulation of the heart dynamics where the activation functions for the heart model are derived from the measured electrocardiogram (ECG) signal recording. The model is developed based on lumped mass nonlinear differential equations that can capture the coupled mechanical and physiological actions of the heart chambers, valves, pulmonary and systemic blood circulation loops. The model was implemented in Matlab/Simulink environment and tested using signals in MGH/MF Waveform Datasets from PhysioNet database. The results show that the model was able to discern the effect of variations in the electrical activations, as captured by ECG features on other heart signals, including the profiles of instantaneous pressure and volumes in different chambers and circulations. In specific, the time and frequency patterns of the right atrium and pulmonary blood pressure signals from the model closely match with the real measurements of arterial and pulmonary blood pressure, respectively. Furthermore, the model-derived pulmonary vein pressure matches with measured respiratory impedance signals. These findings support the suitability of developing a virtual instrument platform where the model-derived signals (presented appropriately) are used for clinical diagnostic in lieu of expensive instrumentations. In addition, the causal relationships between variations in ECG and the model outputs, such as pressure and volume signals, suggest definitive diagnosis methods for certain cardiovascular pathologies which are not easy to diagnosis from-- the ECG patterns.
机译:由于心血管疾病已经成为导致人类死亡的主要原因,因此,近年来心血管系统的定量建模,包括其化学,电和肺机制之间的动态耦合,引起了人们的极大兴趣。当前的动态模型在临床上几乎没有相关性,因为它们无法与来自人心脏的实时信号相关联。这项研究提出了一种实时仿真心脏动力学的新方法,其中心脏模型的激活函数是从测得的心电图(ECG)信号记录中得出的。该模型是基于总质量非线性微分方程开发的,该方程可以捕获心脏腔,瓣膜,肺和全身血液循环回路的耦合机械和生理作用。该模型在Matlab / Simulink环境中实现,并使用PhysioNet数据库的MGH / MF波形数据集中的信号进行了测试。结果表明,该模型能够辨别出ECG功能在其他心脏信号上捕获的电激活变化的影响,包括不同心室和循环中的瞬时压力和体积分布图。具体而言,来自模型的右心房和肺部血压信号的时间和频率模式分别与动脉和肺部血压的实际测量值紧密匹配。此外,模型导出的肺静脉压力与测得的呼吸阻抗信号相匹配。这些发现支持开发虚拟仪器平台的适用性,在该平台上,使用模型衍生的信号(适当显示)代替昂贵的仪器用于临床诊断。此外,心电图变化与模型输出(例如压力和体积信号)之间的因果关系建议了针对某些心血管疾病的明确诊断方法,这些方法不易从以下方面进行诊断: -- 心电图模式。

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