Cardiovascular adaptation to simulated microgravity and countermeasure efficacy assessed by ballistocardiography and seismocardiography

Jeremy Rabineau, Amin Hossein, Federica Landreani, Benoit Haut, Edwin Mulder, Elena Luchitskaya, Jens Tank, Enrico G Caiani, Philippe van de Borne, Pierre-François Migeotte, Jeremy Rabineau, Amin Hossein, Federica Landreani, Benoit Haut, Edwin Mulder, Elena Luchitskaya, Jens Tank, Enrico G Caiani, Philippe van de Borne, Pierre-François Migeotte

Abstract

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 ([Formula: see text]) was computed on each dimension over the cardiac cycle. At the end of HDBR, BCG rotational [Formula: see text] and SCG transversal [Formula: see text] 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 [Formula: see text] 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 VO2 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.

Conflict of interest statement

A.H. and P.F.M are co-founders and hold shares of HeartKinetics, a company specialized in cardiac monitoring. The other authors declare no competing interests.

Figures

Figure 1
Figure 1
General overview of the ESA-RSL bed rest study. BDC baseline data collection, HDT head-down tilt.
Figure 2
Figure 2
A schematic representation of the different elements of CARDIOVECTOR-1. (a) ECG/ICG electrodes; (b) PTG sensor (nasal thermistor); (c) SCG sensor at the cardiac apex (dorsoventral linear accelerations); (d) BCG sensor between the second and the third lumbar vertebrae (3-axis linear accelerations and 3-axis angular velocities); (e) Main unit (connection and amplification).
Figure 3
Figure 3
Longitudinal evolution of portable cardiac monitoring metrics along the ESA-RSL study: (A) Heart rate (bpm); (B) iKzSCG during diastole (µJ.s); (C) iKLinBCG during a complete cardiac cycle (µJ.s); (D)iKRotBCG during a complete cardiac cycle (µJ.s). Results are presented as median [Q1; Q3].
Figure 4
Figure 4
Scatter plot of the per-subject HDT trends for stroke volume (SV) and iKLinBCGsys in the CTRL and JUMP groups. Baseline records are considered as time = 0. Correlation result is expressed as Pearson correlation coefficient R and p-value.

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