Digital Twin-Based Investigation of Seismocardiogram Sensitivity to Tissue Mechanics and Myocardial Motion
Executive Summary
This study employs finite element modeling (FEM) to simulate seismocardiography (SCG) signals by tracking myocardial wall motion and its propagation through thoracic tissues. Using 4D CT scans, the authors developed subject-specific computational models incorporating anatomical structures such as lungs, ribcage, muscles, and adipose tissue. Sensitivity analyses revealed the impact of tissue thickness, stiffness, and myocardial displacement on SCG waveform characteristics, highlighting the importance of personalized anatomical modeling for accurate cardiovascular monitoring. Key cardiac events were validated using CT images and left ventricular volume changes, demonstrating the physiological fidelity of the model.
Answer Machine Insights
Q: How does fat thickness affect SCG signal amplitude?
Increasing fat thickness reduces SCG amplitude due to increased damping effects.
Increasing the fat thickness to 55 mm led to a maximum reduction of 22.8% in the first peak-to-peak amplitude and 11.4% in the second.
Q: What is the impact of myocardial displacement amplification on SCG signals?
Amplifying myocardial displacement increases SCG signal energy and introduces additional dominant frequencies.
The 1.5× magnification resulted in a substantial increase in signal energy, with the power at the first dominant frequency rising by 116%.
Key Results
Increasing fat thickness reduced SCG amplitude by up to 22.8% for the first peak and 11.4% for the second peak.
Amplifying myocardial displacement by 1.5× increased SCG signal energy at dominant frequencies by up to 116%.
Visual Evidence
Clinical Snapshot
Evidence Rating
Relevance
high Priority