Life-Signs Determination Model for Warfighter Physiological Status Monitoring

摘要

The U.S. Army is leading an effort for a Warfighter Physiological Status Monitoring (WPSM) system that interprets data from a suite of wearable physiological sensors to infer a soldier's current health status on the battlefield. The future WPSM system will consist of a body-worn network of biosensors with a central processing control unit whose firmware contains a probabilistic Bayesian Network for assessing the soldier's physiological status. The Bayesian Network will assess the status of the soldier in terms of Life-Signs Presence, Absence or Unknown (PAU) state. Together with this health status assessment, another goal of the Bayesian Network will be to assess the related level of confidence in the diagnosis as resulting from clinical uncertainty, sensory information patterns and reliability of the hardware. This information will be made available to field medics and others over separate communication channels, in order to help prioritize the urgency of medical assistance and evacuation. This paper describes the current development of the PAU Determination Model, which demonstrates the various techniques that will be adopted in the final version of the Bayesian Network to fulfill the health status assessment goals and highlights the robustness of the approach.