Objective: to develop quantitative methods for the clinical interpretation of
the ballistocardiogram (BCG). Methods: 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. Results: 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. Conclusion: 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. Significance:
this work provides a quantitative framework for the clinical interpretation of
BCG signals and the optimization of BCG sensing devices. The present study
considers an average human body and can potentially be extended to include
variability among individuals
