The theory of ballistocardiography-inspired sensing leverages principles of physics and physiology to provide a quantitative, predictive framework that describes the repetitive motion of the human body due to sudden ejection and motion of blood at each heartbeat. Our group developed a closed loop model of cardiovascular hemodynamics to simulate the ballistocardiogram (BCG) as the human barycenter motion through the cardiac cycle and predict BCG changes in pathological conditions, such as reduced contractility and increased stiffness of the left ventricle. The model predictions were tested and confirmed on healthy individuals in a laboratory, as well as swine models before and after induced myocardial infarction. The feasibility and reproducibility of the theory-informed BCG-sensing has also been tested in the Surgical Intensive Care Unit (SICU). The use of BCG-sensing for personalized estimates of cardiovascular parameters was explored using an evolutionary algorithm. The method also provided an estimate of blood pressure that is in good agreement with the cuff-based measurements. For almost 20 years, our group has utilized BCG-inspired sensing to monitor the health of elderly individuals. The goal has been to design sensors that work within the environment, without requiring active participation of the individual. These systems helped identify meaningful deviations and support timely interventions. Sustained increases in heart rate and respiration rate, along with changes in variability, have been associated with early stages of Congestive Heart Failure exacerbation. Signal patterns indicative of fluid accumulation and respiratory compromise have enabled detection of edema and breathing difficulties before clear clinical symptoms appear. In addition, elevated heart rate combined with reduced time spent in bed has been linked to Urinary Tract Infection, reflecting early physiological stress and increased restlessness. These findings demonstrate the scalability of BCG sensing in support of timely intervention, improved care efficiency, and reduced risk of acute deterioration and hospitalization.