Journal article : Review
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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.5MB, Terms of use)
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- Publisher copy:
- 10.1038/s41746-025-02254-1
Authors
+ National Institute of Mental Health
More from this funder
- Funder identifier:
- https://ror.org/04xeg9z08
- Publisher:
- Nature Research
- Journal:
- npj Digital Medicine More from this journal
- Volume:
- 9
- Issue:
- 1
- Article number:
- 74
- Publication date:
- 2025-12-24
- Acceptance date:
- 2025-12-04
- DOI:
- EISSN:
-
2398-6352
- ISSN:
-
2398-6352
- Language:
-
English
- Keywords:
- Subtype:
-
Review
- Pubs id:
-
2374488
- UUID:
-
uuid_294976b8-2e05-4ddf-8707-75df014141c5
- Local pid:
-
pubs:2374488
- Source identifiers:
-
3689070
- Deposit date:
-
2026-01-23
- ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.
Terms of use
- Copyright date:
- 2025
- Licence:
- CC Attribution (CC BY)
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