This paper is now published in Nature Scientific Reports (open access link).
We identify predictors of neurobehavioral alertness over the course of a 6-month spaceflight mission, using self-reported, cognitive, and environmental data collected from 24 astronauts on the International Space Station.
Using time-varying and discordantly-measured environmental, operational, and psychological covariates, we propose an ensemble prediction model to accurately and dynamically predict neurobehavioral alertness at the individual level. Our method is broadly applicable to environmental studies where the main goal is accurate, individualized prediction of human behavior involving a mixture of person-level traits and irregularly measured time series.
Code documentation for “Dynamic Ensemble Prediction of Cognitive Performance in Space” can be found at https://danni-tu.github.io/TRISH_dynamic_prediction/.