Monitoring, Learning and Optimizing Crew Health and Performance

nbsp;We propose to develop and demonstrate an artificial intelligence / machine learning (ML) algorithm which will reveal insights into astronaut health and performance, whichnbsp;in turn can be used to reduce mission risk, and optimize spacecraft resources and limited astronaut time during the mission. The proposed MLnbsp;algorithm can be applied to any astronaut biometric data including heart rate, blood oxygen, temperature, nutrition in consumed food, environmental control system parameters, and injury and illness reports to better inform astronauts and the Mission Control Center with actionable insights made available in real time. Patterns in these data can indicate that astronauts are not at peak physical or mental performance, and patterns in these data sets can suggest how to return the astronauts to peak performance.This algorithmnbsp;can provide critical insights to astronauts by recognizing subtle patterns that appear across many telemetry channels. For example, this algorithm could track metabolic activity in crew in real time and suggest changes to environmental system parameters to maintain constant CO2 levels in a most resource-efficient way.nbsp;Another example is early warning of dangerous conditions (precursors to hypercapnia).nbsp;Its diagnostic power liesnbsp;in its ability to learn in real time, and also in its ability to find subtle correlations between multiple bio parameters in data telemetry available to it. This algorithm also has the added benefit of fast learning for adapting to nuances between astronauts#39; metabolic profiles and finding new diagnostic correlations in real time during the mission.As NASA sends crew out to the Moon and beyond to deep space and Mars, the lack of a quick return to Earth means early diagnosis of physical and mental health problems could mean the difference between life and death.nbsp;This algorithm is compatible with low power hardware so it can be performed onboardnbsp;spacecraft in deep space where there is limited data connectivity to Earth.