A-PLR: An Activity-Aware Assistant for Accurate and Usable Passive Leg Raise Tests in the Smart ICU

The Passive Leg Raise (PLR) test serves as an essential diagnostic instrument for evaluating fluid responsiveness within intensive care units (ICUs). Nevertheless, its execution and interpretation are susceptible to errors resulting from procedural complexity and clinician workload. We introduce A-PLR, an activity-aware assistant integrated into a smart ICU setting to mitigate these challenges. The system employs computer vision and spatial activity recognition to autonomously identify PLR phases, ensure procedural compliance, and provide real-time decision support via an intuitive bedside interface. This paper reports a mixed-method evaluation of A-PLR, comprising both quantitative performance metrics and qualitative insights from clinical professionals (N = 30). Within the controlled experimental setting, the results indicate improved usability and procedural support, as well as indications of enhanced diagnostic assistance and reduced cognitive load when clinicians were supported by A-PLR. In addition, user feedback highlights the potential of activity-aware, AI-driven systems to support decision-making and streamline workflow integration in (simulated) critical care environments.