What Is a Correct Output by Generative AI From the Viewpoint of Well-Being? – Perspective From Sleep Stage Estimation –

Abstract

This paper explores an answer to the question of “what is a correct output by generative AI from the viewpoint of well-being?” and discusses an effectiveness of taking account of a biological rhythm for this issue. Concretely, this paper focuses on an estimation of the REM sleep stage as one of sleep stages, and compared its estimations based on random forest as one of the machine learning methods and the ultradian rhythm as one of the biological rhythms. From the human subject experiment, the following implications have been revealed: (1) the REM sleep stage is wrongly estimated in many areas by random forest; and (2) the integration of the REM sleep stage estimation based on the biological rhythm with that based on random forest improves the F-score of the estimated REM sleep stage.