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

Bipolar Disorders (55) Viewpoints and Perspectives (484)

Published on in Vol 7, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14267, first published .
Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder

Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder

Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder

Authors of this article:

Henning Daus1, 2 Author Orcid Image ;   Timon Bloecher3 Author Orcid Image ;   Ronny Egeler4 Author Orcid Image ;   Richard De Klerk5 Author Orcid Image ;   Wilhelm Stork6 Author Orcid Image ;   Matthias Backenstrass1, 7 Author Orcid Image
Article Authors Cited by (3) Tweetations (1) Metrics

Journals

  1. Sheikh M, Qassem M, Kyriacou P. Wearable, Environmental, and Smartphone-Based Passive Sensing for Mental Health Monitoring. Frontiers in Digital Health 2021;3 View
  2. DAUS H, FINK-LAMOTTE J, BACKENSTRASS M. Mobile-based, emotion-sensitive video diaries and ambulatory third-party assessments as indicators of mood states in bipolar disorder. Minerva Psychiatry 2022;63(4) View
  3. Chia A, Zhang M. Digital phenotyping in psychiatry: A scoping review. Technology and Health Care 2022;30(6):1331 View