TECHNOLOGY AREA(S): Human Systems
OBJECTIVE: Develop multimodal wearable monitoring devices integrated with artificial intelligence-based decision aids for tracking biophysiological states, including cognitive, in the presence of various environmental and physiological stressors.
DESCRIPTION: The explosion of new wearable medical monitoring devices, miniaturized sensors, and artificial intelligence is providing new opportunities to optimize human performance and mitigate the effects of stressors that degrade performance and health within operational settings. Taking inspiration from the use of these technologies for improving the performance of professional athletes, the Department of Defense intends to optimize warfighter performance using similar techniques. The purpose of this topic is to explore technologies that will make tomorrow’s warfighter faster, smarter, and stronger than their adversaries.The human performance focus area involves all aspects of cognition and decision-making, physiology and ergonomics, and the integrating technologies required to support a fully optimized, capable soldier; acting within a given operational setting. The goal of this is the optimization of individual and team performance in combat environments using a range of solutions, scalable across all leadership levels and command echelons. Human performance emphasizes the need to expand Warfighter capabilities while mitigating Warfighter limitations as they apply in combat.To ensure mission superiority, the information about a Soldier’s mind-body state must be successfully acquired and understood within the context of the Warfighter’s cognitive capacity being stressed by fatigue, heat, altitude, interruptions, etc. This challenge is further magnified when a team or multiple teams are required to act together on the same mission. Methods and processes need to be explored that enhance peer-to-peer collaboration, shared situation awareness, and rapid decision making.In the field, warfighters are exposed to a complex set of stressors affecting their physical and cognitive abilities; often altering their physiological well-being (e.g., sleep deprivation, biological rhythm changes, heavy equipment loads, demanding physical tasks, extreme weather/environmental conditions, and inadequate/improper nutrition). The impact of many of these stressors on performance is poorly understood and their combined effects on health and combat effectiveness are virtually unknown. Furthermore, what little is known about the mitigating effects of training and self-management on physical and physiologic viability has not been rigorously applied to the challenge of enhancing Warfighter performance nor has it been demonstrated to be viable in operational or synthetic training environments.There is a need for a novel wearable monitoring solution to promote sustained performance and Warfighter health while helping to offset: 1) training related injuries during physical training across operational environments; 2) fatigue and other performance decrements in extreme environments combined with other stressors; 3) combat performance decrements related to sleep quality, sleep deprivation and sustained operations; 4) impacts of individual stress reactions during performance of operational tasks on overall warfighter health.Gap 1: Insufficient understanding of individual physiological performance markers. Gap 2: Insufficient understanding of the interaction between physical environment (stress, noise, fatigue hydration) and cognitive demands (workload, multitasking, and interruptions) on combat readiness and performance Gap 3: Inadequate automation methods to support information gathering, analysis, and processing leading to more effective and timely decisions at every command echelon.
PHASE I: Identify the proper form factor of a multimodal biophysiological wearable solution for combat and training environments. This solution should be evaluated for the appropriate sensors required to enable accurate classification of biophysiological states (e.g. from cardiac, respiratory, ambulatory and/or neural) and physical activities (running and climbing, etc). Continued evaluation of materials used in the form factor for strength and durability should begin during Phase I and can continue into Phase II.
PHASE II: Develop artificial intelligence algorithms for classification of multi-sensor biophysiological data while a subject is performing complex motion under varying environmental conditions. Customized sensors for motion and altitude may be required here. Phase II should include a pilot study to validate classification accuracy while the device is being worn during strenuous physical activities. Data analysis and classification should begin with the goal of identifying the appropriate state-space for providing individualized biophysiological state assessment.
PHASE III: Establish methods and conduct focused studies to measure sets of biophysiological markers, classify mind-body states related to performance and incorporate an artificial intelligence-based decision aid to provide performance augmentation and resilience recommendations. This will require a population of individuals from within the appropriate environment and age group. The studies will require the establishment of baselines on individuals with further ‘deep dives’ in simulated environments.
KEYWORDS: Human Performance, Physical Training, Wearable Technology, Medical Wearables, Physiological Performance Markers
Karl E. Friedl, “Military applications of soldier physiological monitoring” Journal of Science and Medicine in Sport, Volume 21, Issue 11, November 2018, Pages 1147-1153; Thomas Wyss et al, “The comfort, acceptability and accuracy of energy expenditure estimation from wearable ambulatory physical activity monitoring systems in soldiers”, Journal of Science and Medicine in Sport, November 2017, Volume 20, Supplement 2, Pages S133–S134; Gina Pomranky-Hartnett et al, Army Research Lab Aberdeen Proving Ground MD Human Research And Engineering Directorate, “Soldier-Based Assessment of a Dual-Row Tactor Display during Simultaneous Navigational and Robot-Monitoring Tasks”; Final Report, 1 Feb 2014-31 Mar 2015, DTIC Accession Number ADA623857; Patricia Kime, “Engineering Supersoldiers: Boost In Lethality May Come From Within”, https://www.ausa.org/articles/engineering-supersoldiers-boost-lethality-may-come-within, Oct 24, 2018; Lauren Fish and Paul Scharre, “The Soldier’s Heavy Load” https://www.cnas.org/publications/reports/the-soldiers-heavy-load-1, Sept 26, 2018