Extracting daytime-dependent alertness patterns from mobile game data

Abstract

Cognitive performance fluctuates throughout the day partly due to our "inner clock". Systems that are aware of these fluctuations can adapt to their users' momentary capacity and adjust task difficulty accordingly. Here, we evaluate the use of performance measures obtained from mobile game data to estimate players' varying alertness. We developed a smartphone game that emulates three validated tasks for cognitive performance and conducted an in-the-wild study over two weeks with 30 participants to collect performance measures and subjective ground truth on alertness levels. Our results show that players' performance can be explained by a generative model which is based on two established alertness-modulating processes, namely the homeostatic process and circadian alertness fluctuations. Our method can be used to implicitly model players' alertness levels as a basis for cognition-aware applications.