Wearables can continuously monitor the health of service members, but implementation at scale is hindered by data access, platform incompatibilities, security requirements, and resource constraints. To overcome these challenges and capitalize on rapidly improving technology, solutions must be flexible to support different devices, stable across software updates, and able to operate in harsh environments under resource constraints. Solutions should also consider the competing physical and cognitive demands that users are operating under, as well as their varying levels of medical expertise. The Architecture for Localized Precision Health data Acquisition from Wearables (AlphaWear) was designed using the Modular Open Systems Approach. The platform consists of loosely coupled, severable modules that can be implemented as a whole or by integrating with other systems. High-fidelity data from wearables are sent directly to AlphaWear; the platform can also access vendor-provided metrics over the Internet. AlphaWear harmonizes the data and extracts metrics using published routines. Algorithms synthesize the data into scores that indicate the risk for different health conditions, and dashboards allow users to interact with the data. AlphaWear was deployed to monitor (1) heat strain risk during field exercises, (2) infection risk in a garrison-style environment, and (3) mental health. The system was tested using different pairing configurations and operational constraints. AlphaWear provides a modular framework for using wearables to enable service members to understand their health. AlphaWear can substitute for multiple vendor apps and pull data directly to a designated endpoint. Health metrics have been developed that can be used by a variety of algorithms. The same health algorithms and models can be run using data from different wearables and do not need to be retrained when switching devices. This flexibility enables AlphaWear to be deployed in a variety of environments to monitor several health conditions.
Hegarty‐Craver et al. (Mon,) studied this question.