Gauging situation awareness by the complexity of personnel movement

Introduction: Sailors assigned to Warships endure heavy operational workloads, shift work, and austere, challenging sleeping environments. Decision-support tools that provide real-time monitoring and management of crew endurance can provide critical support in identifying and mitigating these threats. Existing attempts to address these issues are limited, relying on self-assessment, and placing the reporting burden on Sailors. The goal of this research program is to test the feasibility of a monitoring capability that blends Sailor biometric data with contextual indicators to create a summary of fatigue and crew endurance status. Methods: This study is ongoing, with two completed underway data collections on United States Navy warships (n = 535). Volunteers are active-duty Sailors/Marines who wear two devices (the Fatigue Science Readiband and Oura Ring) and answer questions daily that capture contextual health and behavioral data. Using Smartabase (a data aggregation and visualization/dashboard platform), self-report data are combined with wearable biometric data [e.g., heart rate (HR) and HR variability, skin temperature deviation, body movement, sleep]. Results: Identifying problematic cases requires detecting anomalous cases. Within a dashboard, trend data may be particularly useful. For example, Fig. 1 illustrates what a Commanding Officer could see in a dashboard for daily crew sleep at the department level. On average, participants slept 6 hrs/day (less than the 7 hours required per Navy guidelines), but Sailors in engineering routinely obtained closer to 5 hrs/day. At the individual level, threshold-based alerts can prompt action towards a specific Sailor. For example, one Sailor flagged on multiple physiological health indicators (deviation from previous days, as measured by z-scores: temperature deviation > 5, respiration > 4, lowest HR > 2). This individual also self-reported cough, headache, and brain fog symptoms. On previous days, this Sailor had reported “poor” sleep and multiple sleep disturbances. Discussion/conclusions: Though this research is ongoing, several insights are emerging. Group level data may be important for visualizing overall trends while individual level data may be used to draw attention to specific problematic cases that warrant direct follow-up. To establish useful criteria for the flag alert system, contextual data must be used to help interpret wearable data and to develop a deeper understanding of individual phenotypic profiles. Finally, dashboard value ultimately depends on making wearable information actionable, and that can only come from direct engagement and buy-in from leadership and crew. Disclaimer: I am an employee of the U.S. Government. This work was prepared as part of my official duties. Title 17, U.S.C., §105 provides that copyright protection under this title is not available for any work of the U.S. Government. Title 17, U.S.C., §101 defines a U.S. Government work as a work prepared by a military Service member or employee of the U.S. Government as part of that person’s official duties. This work was supported by JPC-5 under work unit no. N2017. The views expressed in this abstract reflect the results of research conducted by the author(s) and do not necessarily reflect the official policy or position of the Department of the Navy, Department of Defense, nor the U.S. Government. The study protocol was approved by the Naval Health Research Center Institutional Review Board in compliance with all applicable Federal regulations governing the protection of human subjects. Research data were derived from an approved Naval Health Research Center Institutional Review Board protocol number NHRC.2021.0003.