Enabling Robust Detection of Cardiac Timing Intervals During Hemorrhage While in the Presence of Military Vehicle Vibrations

Uncontrolled hemorrhaging is a time-sensitive condition that affects military and civilian populations, necessitating the need for timely blood loss evaluations during prehospital care. These evaluations have been shown to be correlated with hemodynamic parameters accessible using the seismocardiogram (SCG), a noninvasively measured cardiac signal. However, SCG usage for hemorrhage control during transport in prehospital care vehicles is difficult due to the environmental vibrations affecting signal quality which is not easily verifiable. In this work, we test if pertinent SCG features could be detected in the presence of military vehicle artifacts. Using a novel simulated and realistic data collection approach with multiple vehicles, we applied robust denoising and feature extraction algorithms to improve SCG feature detection accuracy. We determined that this data collection approach is effective for testing vibrational artifacts and that detection accuracy is drastically improved across all tested vehicles after applying our processing pipeline, This suggests that SCG processing algorithms can be tested in this manner, and such processing pipeline would enable the SCG to be used in uncontrolled settings.