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This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (3574) New Methods (1201) Obstetrics, Gynecology, and Reproductive Medicine (353) Tools, Programs and Algorithms (423) mHealth for Data Collection and Research (1286) Sleep Monitoring, Sleep Quality, Sleep Disorders (289)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55834, first published .
iPhone app displays temperature data next to a small white device

Novel Methodology for Identifying the Occurrence of Ovulation by Estimating Core Body Temperature During Sleeping: Validity and Effectiveness Study

Novel Methodology for Identifying the Occurrence of Ovulation by Estimating Core Body Temperature During Sleeping: Validity and Effectiveness Study

Authors of this article:

Daisuke Sato1 Author Orcid Image ;   Koyuki Ikarashi1 Author Orcid Image ;   Fumiko Nakajima1 Author Orcid Image ;   Tomomi Fujimoto1 Author Orcid Image
Article Authors Cited by (1) Tweetations (3) Metrics

Journals

  1. Shi Y, Wang C, Yang Y, Li Q, Chung P, Wang Y. The diagnostic accuracy of wearable digital technology in detecting fertility window and menstrual cycles: a systematic review and Bayesian network meta-analysis. npj Digital Medicine 2026;9(1) View