Harnessing the Manifold Structure of Cardiomechanical Signals for Physiological Monitoring during Hemorrhage.

OBJECTIVE Local oscillation of the chest wall in response to events during the cardiac cycle may be captured using a sensing modality called seismocardiography (SCG), which is commonly used to infer cardiac time intervals (CTIs) such as the pre-ejection period (PEP). An important factor impeding the ubiquitous application of SCG for cardiac monitoring is that morphological variability of the signals makes consistent inference of CTIs a difficult task in the time-domain. The goal of this work is therefore to enable SCG-based physiological monitoring during trauma-induced hemorrhage using signal dynamics rather than morphological features. METHODS We introduce and explore the observation that SCG signals follow a consistent low-dimensional manifold structure during periods of changing PEP induced in a porcine model of trauma injury. Furthermore, we show that the distance traveled along this manifold correlates strongly to changes in PEP (δPEP). RESULTS δPEP estimation during hemorrhage was achieved with a median R2 of 92.5% using a rapid manifold approximation method, comparable to an ISOMAP reference standard, which achieved an R2 of 95.3%. CONCLUSION Rapidly approximating the manifold structure of SCG signals allows for physiological inference abstracted from the time-domain, laying the groundwork for robust, morphology-independent processing methods. SIGNIFICANCE Ultimately, this work represents an important advancement in SCG processing, enabling future clinical tools for trauma injury management.