We implemented the resulting model and the psychomotor vigilance test as a smartphone application ( 2B‐Alert App), and prospectively validated its performance in a 62‐hr total sleep deprivation study in which 21 participants used the app to perform psychomotor vigilance tests every 3 hr and obtain real‐time individualized predictions after each test. We incorporated a Bayesian learning algorithm within the validated Unified Model of Performance to automatically and gradually adapt the model parameters to an individual after each psychomotor vigilance test. Here we describe and validate the 2B‐Alert App, the first mobile application that progressively learns an individual’s trait‐like response to sleep deprivation in real time, to generate increasingly more accurate individualized predictions of alertness. Knowing how an individual responds to sleep deprivation is a requirement for developing personalized fatigue management strategies.
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