Candidate Passive Sensor Suite Technologies for Tactical Combat Casualty Care Environments: Comparative Assessment...

The United States Army Institute for Surgical Research conducted an analysis of 3 prototype sensor suites; all candidates were designed to passively document care delivery in tactical combat casualty care environments.

This study aims to ensure sensor suites remain resilient and adaptive in complex battlefield environments. This research effort conducts a systematic comparative assessment of prototype solutions.

The assessment methodology prioritized functionality, usability, and performance. The assessment consisted of three phases: (1) tabletop evaluations, (2) simulated use testing, and (3) a sensor suite rodeo simulation event. The second and third phases included human participants leveraging the technology prototypes in hyperrealistic tactical combat casualty care simulation environments. Additionally, the third phase allowed the researchers to assess the performance of each prototype in a range of operational environmental lighting conditions.

During the tabletop evaluation phase, all 3 prototype sensor suite solutions demonstrated acceptable results (≥1) in the technical specification assessment. The 2-part heuristic analysis revealed variability, where the least complex configurations received the highest assessment scores. To capture and record raw data, scores ranged from 44.6 to 87 on a 100-point scale. To offload and export the raw data, scores ranged from 22.9 to 87.5 on a 100-point scale. During simulated user testing, all 3 sensor suites achieved passing quantitative scores (≥60); the system usability scores (SUS) ranged from 60 to 85 on a 100-point scale. More complex technology configurations received higher usability scores. From a qualitative perspective, vital sign monitor latency display issues led to reliability concerns. All 3 prototypes successfully generated raw data; the individual outputs ranged from 0.06 to 0.13 GB/minute. During the sensor suite rodeo simulation event, all 3 sensor suites achieved passing quantitative scores (≥60); the SUS ranged from 66.7 to 86.7 on a 100-point scale; the most complex technology prototype configuration scored higher. Qualitative findings identified data transfer issues with large file sizes and pairing issues with vital sign monitors. All 3 prototypes successfully generated raw data; the individual outputs varied (ranging from 0.012 to 0.24 GB/min) based on the environmental lighting conditions (full sun, indoor lighting, and low light). However, from a data quality perspective, only 1 camera component produced viable video data in all 3 environments.

The comparative assessment revealed opportunities to combine the strengths of both approaches in a next-generation implementation. This preliminary assessment was constrained by several factors: (1) effective tracking of consumable medical supplies, (2) advancement of artificial intelligence algorithms to process the raw data, and (3) ability to manage multiple casualties or patients. Follow-on evaluations are needed to address these limitations. This systematic, 3-part methodology evaluates early-stage sensor suite prototypes and provides a reproducible framework for advancing battlefield medical technologies.