Wearables at the Edge for Monitoring Warfighter Health and Readiness

In the proposed program, we will develop and implement a secure framework for low-power acquisition, processing and analysis of physiological and environmental sensor signals from wearable devices. The multi-parameter signals will be used to effectively monitor the warfighter’s health and operational readiness at the edge. We will accomplish the program objective by leveraging the advancements in processing and power management in modern consumer-driven wearable devices and smartphones. The framework involves the optimal distribution of the computational requirements over the hierarchical computational resources in the devices. This will involve optimal implementation of software in low-power microcontrollers (MCU) as well as high-performance application processors (AP). It also involves the separation of computational tasks between different devices (e.g., between smartwatch and smartphone). The framework will include the implementation of application programming interfaces (API) that allows efficient implementation of signal processing and algorithms. Based on the framework for data acquisition, processing, and analysis, we will build a health anomaly detection system. The system will passively and continuously identify health anomalies based on continuous physiological and environmental sensor data. We will evaluate the system while the warfighter is engaged in various activities expected during operational deployment, ranging in activity levels from sleep and rest to engagement in battlefield scenarios. The system will be tested with warfighters in a healthy state, as well as in scenarios that involve the onset of serious medical conditions that can be encountered in battlefield environments. The overall objective is to support DoD’s requirement to monitor and assess the warfighter’s health and operational readiness, based on physiological and environmental sensor data from wearable devices at the edge.