Cardiovascular diseases remain the leading cause of mortality worldwide, highlighting the need for improved monitoring and diagnosis techniques. While chest wall displacement reflects cardiac mechanical activity, conventional monitoring lacks the spatial resolution to characterize these displacements under various conditions. This study introduces a displacement-based finite element (FE) framework to simulate and analyze cardiac-induced chest wall motion using ECG-gated cardiac computed tomography data. Subject-specific cardiac motion was extracted via an optical flow algorithm and prescribed as a boundary condition to a thoracic FE model. This approach enables the computation of spatially resolved displacement across the chest surface. A 6×6 grid of uniformly distributed points is defined on the anterior chest surface for four healthy subjects, and displacement signals are analyzed over the cardiac cycle. The results reveal consistent spatiotemporal patterns of chest wall motion, with distinct propagation behavior aligned with key cardiac phases and strong correspondence to left ventricular volume dynamics. These results suggest that FE-based simulations can bridge the gap between internal cardiac mechanics and surface-level measurements, providing a physiologically interpretable foundation for next-generation non-invasive cardiac monitoring.