Unobtrusive inference of diurnal rhythms from smartphone data.

ABSTRACT: Diurnal rhythms are an integral feature of psychopathology but difficult to measure at scale. Smartphones are ubiquitous and therefore uniquely positioned to measure such rhythms non-invasively and continuously. Here, we propose a digital phenotyping framework to quantify diurnal rhythms. We use it to predict sleep duration from smartphone typing dynamics and analyse rhythm phase during time zone transitions with a clinical outpatient sample and a year-long longitudinal data set.

SUBMITTER: Knol L 

PROVIDER: S-EPMC12830913 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature