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.

Non-invasive remote detection of cardiac and blood displacements is an important topic in cardiac telemedicine. Here we propose kino-cardiography (KCG), a non-invasive technique based on measurement of body vibrations produced by myocardial contraction and blood flow through the cardiac chambers and major vessels. KCG is based on ballistocardiography and measures 12 degrees-of-freedom (DOF) of body motion. We tested the hypothesis that KCG reliably assesses dobutamine-induced haemodynamic changes in healthy subjects. Using a randomized double-blinded placebo-controlled crossover study design, dobutamine and placebo were infused to 34 volunteers (25 ± 2 years, BMI 22 ± 2 kg/m², 18 females). Baseline recordings were followed by 3 sessions of increasing doses of dobutamine (5, 10, 20 μg/kg.min) or saline solution. During each session, stroke volume (SV) and cardiac output (CO) were determined by echocardiography and followed by a 90 s KCG recording. Measured linear accelerations and angular velocities were used to compute total Kinetic energy (iK) and power (Pmax). KCG sorted dobutamine infusion vs. placebo with 96.9% accuracy. Increases in SV and CO were correlated to iK (r = +0.71 and r = +0.8, respectively, p < 0.0001). Kino-cardiography, with 12-DOF, allows detecting dobutamine-induced haemodynamic changes with a high accuracy and present a major improvement over single axis ballistocardiography or seismocardiography.

Head-down bed rest (HDBR) reproduces the cardiovascular effects of microgravity. We tested the hypothesis that regular high-intensity physical exercise (JUMP) could prevent this cardiovascular deconditioning, which could be detected using seismocardiography (SCG) and ballistocardiography (BCG). 23 healthy males were exposed to 60-day HDBR: 12 in a physical exercise group (JUMP), the others in a control group (CTRL). SCG and BCG were measured during supine controlled breathing protocols. From the linear and rotational SCG/BCG signals, the integral of kinetic energy ( $$iK$$iK ) was computed on each dimension over the cardiac cycle. At the end of HDBR, BCG rotational $$iK$$iK and SCG transversal $$iK$$iK decreased similarly for all participants (− 40% and − 44%, respectively, p < 0.05), and so did orthostatic tolerance (− 58%, p < 0.01). Resting heart rate decreased in JUMP (− 10%, p < 0.01), but not in CTRL. BCG linear $$iK$$iK decreased in CTRL (− 50%, p < 0.05), but not in JUMP. The changes in the systolic component of BCG linear iK were correlated to those in stroke volume and V_O2 max (R = 0.44 and 0.47, respectively, p < 0.05). JUMP was less affected by cardiovascular deconditioning, which could be detected by BCG in agreement with standard markers of the cardiovascular condition. This shows the potential of BCG to easily monitor cardiac deconditioning.

Recent years have witnessed an upsurge in the usage of ballistocardiography (BCG) and seismocardiography (SCG) to record myocardial function both in normal and pathological populations. Kinocardiography (KCG) combines these techniques by measuring 12 degrees-of-freedom of body motion produced by myocardial contraction and blood flow through the cardiac chambers and major vessels. The integral of kinetic energy (iK) obtained from the linear and rotational SCG/BCG signals, and automatically computed over the cardiac cycle, is used as a marker of cardiac mechanical function. The present work systematically evaluated the test–retest (TRT) reliability of KCG iK derived from BCG/SCG signals in the short term (<15 min) and long term (3–6 h) on 60 healthy volunteers. Additionally, we investigated the difference of repeatability with different body positions. First, we found high short-term TRT reliability for KCG metrics derived from SCG and BCG recordings. Exceptions to this finding were limited to metrics computed in left lateral decubitus position where the TRT reliability was moderate-to-high. Second, we found low-to-moderate long-term TRT reliability for KCG metrics as expected and confirmed by blood pressure measurements. In summary, KCG parameters derived from BCG/SCG signals show high repeatability and should be further investigated to confirm their use for cardiac condition longitudinal monitoring.

Objective : To investigate if modern seismocardiography (SCG) and ballistocardiography (BCG) are useful in the detection of hemodynamic changes occurring during simulated obstructive apneic events. Methods : Forty-seven healthy volunteers performed a voluntary maximum Mueller maneuver (MM) for 10 s, and SCG and BCG signals were simultaneously taken. The kinetic energy of a set of cardiac cycles before and during the apneic episode was automatically computed from the rotational and linear channels of the SCG and BCG waveforms and its temporal integral ( i K ) was derived (unit of measure: microjoules per second (µJ·s)). The estimated transmural pressure ( eP _TM ) was assessed as the difference between systemic blood pressure and maximal inspiratory pressure (MIP). The Wilcoxon sign-rank test was used to evaluate differences in energy measurements between normal respiration and the loaded inspiration maneuver. Cardiac kinetic energies and the MIP produced during the MM were compared by linear regression analysis following log transformation in order to assess the correlation between variables. Main results : The i K R o t B C G during normal breathing increased from 1.1(0.8; 1.4) to 1.9(1.4; 4.3) µJ·s during MM ( p < 0.001). Meanwhile, i K Rot SCG increased from 54 (31; 92) to 84 (44; 153) µJ·s, ( p < 0.001). The i K R o t B C G and i K R o t S C G of a set of cardiac cycles during the MM were negatively associated with the MIP ( r: −0.59, p < 0.001 and r: − 0.53, p = 0.001 for i K R o t B C G and i K R o t S C G , respectively). When eP _TM was considered, this association became positive ( r: +0.58, p < 0.001 and r: +0.60, p < 0.001, for i K R o t B C G and i K R o t S C G , respectively). When the i K _LIN was considered as the comparative factor, correlations with the MIP and eP _TM were weak and insignificant. Men had higher values of i K than women. Significance : Simulated obstructive apnea elicits large rotational i K swings, which are related to the intensity of the inspiratory effort and, as such, to the intensity of the left ventricular afterload. Computation of cardiac kinetic energy through BCG and SCG may shed further light on the impact of obstructive respiratory events on the cardiovascular system.

Ballistocardiography (BCG) and Seismocardiography (SCG) assess the vibrations produced by cardiac contraction and blood flow, respectively, by means of micro-accelerometers and micro-gyroscopes. From the BCG and SCG signals, maximal velocities (V_Max), integral of kinetic energy (iK), and maximal power (P_Max) can be computed as scalar parameters, both in linear and rotational dimensions. Standard echocardiography and 2-dimensional speckle tracking imaging echocardiography were performed on 34 healthy volunteers who were infused with increasing doses of dobutamine (5–10–20 μg/kg/min). Linear V_Max of BCG predicts the rates of left ventricular (LV) twisting and untwisting (both p < 0.0001). The linear P_Max of both SCG and BCG and the linear iK of BCG are the best predictors of the LV ejection fraction (LVEF) (p < 0.0001). This result is further confirmed by mathematical models combining the metrics from SCG and BCG signals with heart rate, in which both linear P_Max and iK strongly correlate with LVEF (R = 0.7, p < 0.0001). In this setting of enhanced inotropism, the linear V_Max of BCG, rather than the V_Max of SCG, is the metric which best explains the LV twist mechanics, in particular the rates of twisting and untwisting. P_Max and iK metrics are strongly associated with the LVEF and account for 50% of the variance of the LVEF.