Modeling Seismocardiographic Signal using Finite Element Modeling and Medical Image Processing

Abstract

Seismocardiography (SCG) is the measurement of the chest surface accelerations that are primarily produced by a combination of mechanical activities of the heart, such as valve closures and openings, blood momentum changes and myocardial movements [ 1 – 3 ]. The complex nature of these processes has made it challenging to relate the morphology of the SCG signal to its genesis. Certain studies have used medical imaging to identify several feature points of the SCG signal by correlating their occurrence time with the corresponding cardiac events seen in imaging [4 , 5] . However, these findings remain inconclusive [6] . The localized movements (i.e. valve openings and closures, ventricular contractions, blood flow accelerations etc.) may superimpose causing complex movements where original movements may amplify or nullify as they reach the chest surface and affect SCG morphology. Hence, SCG signal can also be described as the propagated vibrations generated by individual sources (i.e., valve closures and openings, blood flow accelerations). These vibrations displace their more immediate boundaries (e.g., pericardium, Aorta wall) and surrounding tissues (e.g. lung tissue, ribs, chest wall muscle and skin) before they are detected at the chest surface. Hence, modeling the propagation of overall cardiac wall motion to the chest surface may help enhance our understanding of SCG genesis.