Computational and Mechanical Modeling of SCG Signals

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Introduction Seismocardiography (SCG) includes vibration signals propagated to the chest surface from cardiac valve movement, blood flow and myocardial muscle contraction. SCG feature analysis may prove useful in the early non-invasive detection of HF deterioration. In this study, the propagation and coupling of cardiac surface motion to the anterior chest surface was modeled using computer simulations. Objective Develop a computational model of SCG propagation to enhance understanding of SCG genesis, and SCG's spatial amplitude and spectrographic distribution over the anterior chest wall. Methods The computational geometry was extracted from short-axis cardiac cine MRI imaging of a healthy participant. Cardiac wall motion was captured by applying a 3D motion tracking algorithm to the cine MRI images. The propagation of cardiac motion to the chest surface was simulated using Finite Element Method (FEM). A mechanical model was also developed where the displacements at a simulated heart wall were coupled to a mechanical chest surface model using an array of linear actuators. Results Common SCG feature points (e.g., MC-mitral valve closure; IM- Isovolumic contraction; AO- aortic valve opening; AC- aortic valve closure; and MO- mitral valve opening) were predicted by the model. Furthermore, the timing of these feature points was validated against the left ventricle volume variation extracted from short-axis cine MRI images. The maximum SCG amplitude (in the dorso-ventral direction) was observed in the 4th intercoastal space near the left lower sternal border. The pilot results of the mechanical model were in a qualitative agreement. Conclusions The computer model predicted the feature points observed in real SCG measurements. The current model may be utilized in the future to study the distribution of SCG over precordium and to analyze the effect of the properties of cardiac and contiguous chest structures, including great vessels, chest wall ribs, muscles and articulations, lungs, and cutaneous soft tissue. Further model development may deepen understanding of SCG generation and propagation, increasing its potential utility for diagnosis and monitoring of cardiac pathologies.