Ballistocardiography (BCG) and seismocardiography (SCG) are non-invasive techniques used to record the micromovements induced by cardiovascular activity at the body’s center of mass and on the chest, respectively. Since their inception, their potential for evaluating cardiovascular health has been studied. However, both BCG and SCG are impacted by respiration, leading to a periodic modulation of these signals. As a result, data processing algorithms have been developed to exclude the respiratory signals, or recording protocols have been designed to limit the respiratory bias. Reviewing the present status of the literature reveals an increasing interest in applying these techniques to extract respiratory information, as well as cardiac information. The possibility of simultaneous monitoring of respiratory and cardiovascular signals via BCG or SCG enables the monitoring of vital signs during activities that require considerable mental concentration, in extreme environments, or during sleep, where data acquisition must occur without introducing recording bias due to irritating monitoring equipment. This work aims to provide a theoretical and practical overview of cardiopulmonary interaction based on BCG and SCG signals. It covers the recent improvements in extracting respiratory signals, computing markers of the cardiorespiratory interaction with practical applications, and investigating sleep breathing disorders, as well as a comparison of different sensors used for these applications. According to the results of this review, recent studies have mainly concentrated on a few domains, especially sleep studies and heart rate variability computation. Even in those instances, the study population is not always large or diversified. Furthermore, BCG and SCG are prone to movement artifacts and are relatively subject dependent. However, the growing tendency toward artificial intelligence may help achieve a more accurate and efficient diagnosis. These encouraging results bring hope that, in the near future, such compact, lightweight BCG and SCG devices will offer a good proxy for the gold standard methods for assessing cardiorespiratory function, with the added benefit of being able to perform measurements in real-world situations, outside of the clinic, and thus decrease costs and time.

Seismocardiography (SCG), a method for measuring heart-induced chest vibrations, is gaining attention as a non-invasive, accessible, and cost-effective approach for cardiac pathologies, diagnosis, and monitoring. This study explores the integration of SCG acquired through smartphone technology by assessing the accuracy of metrics derived from smartphone recordings and their consistency when performed by patients. Therefore, we assessed smartphone-derived SCG’s reliability in computing median kinetic energy parameters per record in 220 patients with various cardiovascular conditions. The study involved three key procedures: (1) simultaneous measurements of a validated hardware device and a commercial smartphone; (2) consecutive smartphone recordings performed by both clinicians and patients; (3) patients’ self-conducted home recordings over three months. Our findings indicate a moderate-to-high reliability of smartphone-acquired SCG metrics compared to those obtained from a validated device, with intraclass correlation (ICC) > 0.77. The reliability of patient-acquired SCG metrics was high (ICC > 0.83). Within the cohort, 138 patients had smartphones that met the compatibility criteria for the study, with an observed at-home compliance rate of 41.4%. This research validates the potential of smartphone-derived SCG acquisition in providing repeatable SCG metrics in telemedicine, thus laying a foundation for future studies to enhance the precision of at-home cardiac data acquisition.

Severe aortic valve diseases (AVD) cause changes in heart sounds, making phonocardiogram (PCG) analyses challenging. This study presents a novel method for segmenting heart sounds without relying on an electrocardiogram (ECG), specifically targeting patients with severe AVD. Our algorithm enhances traditional Hidden Semi-Markov Models by incorporating signal envelope calculations and statistical tests to improve the detection of the first and second heart sounds (S1 and S2). We evaluated the method on the PhysioNet/CinC 2016 Challenge dataset and a newly acquired AVD-specific dataset. The method was tested on a total of 27,400 cardiac cycles. The proposed approach outperformed the existing methods, achieving a higher sensitivity and positive predictive value for S2, especially in the presence of severe heart murmurs. Notably, in patients with severe aortic stenosis, our proposed ECG-free method improved S2 sensitivity from 41% to 70%.

Microgravity induces profound cardiovascular changes, prompting space agencies to develop countermeasures to preserve their crewmembers’ health. This study aimed to use a portable device based on electro-, impedance- and seismo-cardiography, to monitor a series of cardiovascular features in 17 cosmonauts. Our results showed that the evolution of cardiac time intervals, blood pressure, stroke volume, and cardiac systolic kinetic energy depended on the chosen baseline position. After five months in space, heart rate increased compared to the supine baseline on Earth (p = 0.013, d = 0.86) but not to the sitting position. Similarly, a marker of cardiac contractility (PEP/LVET ratio) decreased relative to the sitting baseline (p = 0.004, d = 1.09) but not the supine reference. All measured features, except heart rate, returned to baseline within three days post-landing. These findings support the efficacy of current countermeasures in facilitating rapid cardiovascular re-adaptation to terrestrial gravity.

Microgravity induces profound cardiovascular changes, prompting space agencies to develop countermeasures to preserve their crewmembers’ health. This study aimed to use a portable device based on electro-, impedance- and seismo-cardiography, to monitor a series of cardiovascular features in 17 cosmonauts. Our results showed that the evolution of cardiac time intervals, blood pressure, stroke volume, and cardiac systolic kinetic energy depended on the chosen baseline position. After five months in space, heart rate increased compared to the supine baseline on Earth (p = 0.013, d = 0.86) but not to the sitting position. Similarly, the ratio of pre-ejection period to left ventricular ejection time (PEP/LVET) decreased relative to the sitting baseline (p = 0.004, d = 1.09) but not the supine reference. All measured features, except heart rate, returned to baseline within three days post-landing. These findings support the efficacy of current countermeasures in facilitating rapid cardiovascular re-adaptation to terrestrial gravity.