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

mHealth for Screening (446) Depression and Mood Disorders; Suicide Prevention (2398) Wearable Devices and Sensors (1533) Validity, Reliability, and Bias (132)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/91479, first published .
Woman checks smartwatch displaying actigraphy data for depressive symptoms detection.

Passive Screening for Depressive Symptoms Using Daily Wrist Actigraphy and Deep Learning: Model Development and Validation Study

Passive Screening for Depressive Symptoms Using Daily Wrist Actigraphy and Deep Learning: Model Development and Validation Study

Authors of this article:

Doljinsuren Enkhbayar1 Author Orcid Image ;   Somin Oh1 Author Orcid Image ;   Jinhee Lee2 Author Orcid Image ;   Min-Hyuk Kim2 Author Orcid Image ;   Erdenebayar Urtnasan3 Author Orcid Image ;   Jaehong Key1 Author Orcid Image
Article Authors Cited by Tweetations (1) Metrics

Doljinsuren Enkhbayar   1 , MS ;   Somin Oh   1 , MS ;   Jinhee Lee   2 , MD, PhD ;   Min-Hyuk Kim   2 , MD, PhD ;   Erdenebayar Urtnasan   3 * , PhD ;   Jaehong Key   1 * , PhD

1 Department of Biomedical Engineering, Mirae campus, Yonsei University, Wonju-si, Gangwan-do, Republic of Korea

2 Department of Psychiatry, Wonju College of Medicine, Yonsei University Mirae Campus, Wonju, Gangwon-do, Republic of Korea

3 Division of AI Semiconductor, Yonsei University Mirae Campus, Wonju, Gangwon-do, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Jaehong Key, PhD
  • Department of Biomedical Engineering
  • Mirae campus, Yonsei University
  • 1, Yeonsedae-gil, Heungeop-myeon
  • Wonju-si, Gangwan-do 26493
  • Republic of Korea
  • Phone: 82 33 760 5270
  • Fax: 82 33 760 2919
  • Email: jkey@yonsei.ac.kr