Bodyseismography (BSG): Theoretical Foundation and Numerical Modeling
Bodyseismography (BSG) records cardiovascular vibrations transmitted through the body and a supporting bed, enabling contactless assessment of cardiac mechanics. Relating these vibrations to hemodynamic features requires separating cardiac excitation from the effects of body and bed transmission. We develop a source-transmission-measurement framework that couples myocardial contraction and vascular recoil to directional BSG observations. The theory connects stroke volume, cardiac output, and blood pressure to observation and target Jacobians, establishes a local first-order target-observability criterion, and characterizes how additional sensing axes reduce ambiguities under specified source and transmission uncertainties. Numerical modeling combines four-chamber cardiac mechanics, cardiac-to-body excitation, and calibrated body-bed operators. Across 27 participants, a multilayer finite-element model with calibrated frequency correction achieves median Pearson correlation coefficients of 0.865 for the vertical channel and 0.682 for the planar-sum channel in matched-window waveform reconstruction. Controlled stroke-volume perturbations show that transmission reshapes feature sensitivity, including a reversal of the vertical feature association in 8 of 27 participant-specific transfer models. These analytical and numerical studies explain how cardiovascular sources and mechanical propagation jointly shape triaxial BSG and provide a physical basis for relating directional vibration features to hemodynamic changes.
Authors
- Zhenlin An (ORCID: https://orcid.org/0000-0003-4120-773X)
- Zixuan Zeng (ORCID: https://orcid.org/0009-0005-7051-7421)
- Yuyan Wu (ORCID: https://orcid.org/0009-0009-3152-939X)
- Hae Young Noh (ORCID: https://orcid.org/0000-0002-7998-3657)
- Wenli Song (ORCID: https://orcid.org/0000-0001-8174-1772)
- Yida Zhang
- Jiayu Chen
- Fei Dou
- Jiahui Li
- Yuanyuan Zhang
- Sahas Biddappa
- Yixuan Li
Institutions
- University of Georgia (US)
- Stanford University (US)
Publication Details
- Journal
- arXiv (Cornell University)
- Published
- 2026-10-26
- DOI
- https://doi.org/10.48550/arxiv.2610.35844
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- preprint