The Navy relies on handling quality ratings (HQRs) for evaluation of its aircraft to ensure that it can maintain, train, and equip combat-ready forces. The aviators perspective is vital for assessing aircraft handling, but can be difficult to obtain from Pilots without distracting them or relying on their memory. Pilot physiological state fluctuates with the amount of workload required to handle the aircraft, making it possible to obtain quantitative measurements of the Pilots experience through physiological sensors. This insight can significantly increase efficacy and efficiency of flight testing, especially when combined with traditional instrumentation, recording, and transmission of aircraft Time-Space-Position-Information during flight and aerobatic maneuvers. To meet this requirement, Charles River Analytics proposes to design and demonstrate the feasibility of a platform for Physiologically Assessed Ratings of Aircraft Operation and Handling (PHARAOH). The PHARAOH effort includes: (1) a flight-compatible sensor suite for measuring Pilot physiology; (2) machine learning algorithms to process, fuse, and interpret physiological data for accurate HQR assessment during flight testing; (3) a UI designed to meet the needs of Flight Test Teams by providing HQRs of aircraft along with the supporting data; and (4) pursuit of suitable transition and commercialization opportunities for PHARAOH technologies.
Benefit: PHARAOH will provide in-flight physiological sensing, processing, and modeling capabilities and data services that can transition into US Government programs of record by providing instrumentation solutions for rotary and fixed-wing aircraft including F-35 variants within the US Navy and other Armed Forces. Incorporating the innovations developed under PHARAOH will increase the efficiency and efficacy of flight testing and free up mission resources. In the private sector, we see opportunities licensing or selling PHARAOH technologies to commercial and military vehicle manufacturers to improve system testing, in-vehicle monitoring, and training. We will also incorporate advances in data processing, and modeling made under this effort to enhance our Sherlock software, increasing its appeal as a commercial product.
Keywords: fNIRS, fNIRS, Physiological Sensing, EMG, Human state assessment, Flight Testing, HRV, EOG, handling quality ratings