IEEE Trans Biomed Eng. 2019 Oct;66(10):2906-2917. doi: 10.1109/TBME.2019.2897952. Epub 2019 Feb 6.
To develop quantitative methods for the clinical interpretation of the ballistocardiogram (BCG).
A closed-loop mathematical model of the cardiovascular system is proposed to theoretically simulate the mechanisms generating the BCG signal, which is then compared with the signal acquired via accelerometry on a suspended bed.
Simulated arterial pressure waveforms and ventricular functions are in good qualitative and quantitative agreement with those reported in the clinical literature. Simulated BCG signals exhibit the typical I, J, K, L, M, and N peaks and show good qualitative and quantitative agreement with experimental measurements. Simulated BCG signals associated with reduced contractility and increased stiffness of the left ventricle exhibit different changes that are characteristic of the specific pathological condition.
The proposed closed-loop model captures the predominant features of BCG signals and can predict pathological changes on the basis of fundamental mechanisms in cardiovascular physiology.
This paper provides a quantitative framework for the clinical interpretation of BCG signals and the optimization of BCG sensing devices. The present paper considers an average human body and can potentially be extended to include variability among individuals.
开发用于临床解读心冲击图(BCG)的定量方法。
提出了一个心血管系统的闭环数学模型,从理论上模拟产生 BCG 信号的机制,然后将其与悬浮床上加速度计获取的信号进行比较。
模拟的动脉压力波形和心室功能与临床文献中报道的情况在定性和定量上都非常吻合。模拟的 BCG 信号显示出典型的 I、J、K、L、M 和 N 峰,与实验测量结果具有良好的定性和定量一致性。与左心室收缩力降低和僵硬度增加相关的模拟 BCG 信号显示出特定病理状态的特征性变化。
所提出的闭环模型捕捉到了 BCG 信号的主要特征,并能够根据心血管生理学的基本机制预测病理变化。
本文为 BCG 信号的临床解读和 BCG 传感设备的优化提供了一个定量框架。本文考虑了一个平均人体,并且有可能扩展到包括个体之间的差异。