Published on in Vol 6, No 11 (2019): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12814, first published .
Wearable Technology for High-Frequency Cognitive and Mood Assessment in Major Depressive Disorder: Longitudinal Observational Study

Wearable Technology for High-Frequency Cognitive and Mood Assessment in Major Depressive Disorder: Longitudinal Observational Study

Wearable Technology for High-Frequency Cognitive and Mood Assessment in Major Depressive Disorder: Longitudinal Observational Study

Journals

  1. Weizenbaum E, Torous J, Fulford D. Cognition in Context: Understanding the Everyday Predictors of Cognitive Performance in a New Era of Measurement. JMIR mHealth and uHealth 2020;8(7):e14328 View
  2. Marsch L. Digital health data-driven approaches to understand human behavior. Neuropsychopharmacology 2021;46(1):191 View
  3. Benjamens S, Dhunnoo P, Meskó B. The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database. npj Digital Medicine 2020;3(1) View
  4. Hafiz P, Bardram J. The Ubiquitous Cognitive Assessment Tool for Smartwatches: Design, Implementation, and Evaluation Study. JMIR mHealth and uHealth 2020;8(6):e17506 View
  5. Patoz M, Hidalgo-Mazzei D, Blanc O, Verdolini N, Pacchiarotti I, Murru A, Zukerwar L, Vieta E, Llorca P, Samalin L. Patient and physician perspectives of a smartphone application for depression: a qualitative study. BMC Psychiatry 2021;21(1) View
  6. Hafiz P, Miskowiak K, Maxhuni A, Kessing L, Bardram J. Wearable Computing Technology for Assessment of Cognitive Functioning of Bipolar Patients and Healthy Controls. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(4):1 View
  7. Müller L, Gossmann K, Schmid R, Rosner R, Unterhitzenberger J, Nater-Mewes R. A pilot study on ecological momentary assessment in asylum-seeking children and adolescents resettled to Germany: Investigating compliance, post-migration factors, and the relation between daily mood, sleep patterns, and mental health. PLOS ONE 2021;16(2):e0246069 View
  8. Yunusova A, Lai J, Rivera A, Hu S, Labbaf S, Rahmani A, Dutt N, Jain R, Borelli J. Assessing the Mental Health of Emerging Adults Through a Mental Health App: Protocol for a Prospective Pilot Study. JMIR Research Protocols 2021;10(3):e25775 View
  9. Hilty D, Armstrong C, Luxton D, Gentry M, Krupinski E. A Scoping Review of Sensors, Wearables, and Remote Monitoring For Behavioral Health: Uses, Outcomes, Clinical Competencies, and Research Directions. Journal of Technology in Behavioral Science 2021;6(2):278 View
  10. Ferrar J, Griffith G, Skirrow C, Cashdollar N, Taptiklis N, Dobson J, Cree F, Cormack F, Barnett J, Munafò M. Developing Digital Tools for Remote Clinical Research: How to Evaluate the Validity and Practicality of Active Assessments in Field Settings. Journal of Medical Internet Research 2021;23(6):e26004 View
  11. Sverdlov O, Curcic J, Hannesdottir K, Gou L, De Luca V, Ambrosetti F, Zhang B, Praestgaard J, Vallejo V, Dolman A, Gomez-Mancilla B, Biliouris K, Deurinck M, Cormack F, Anderson J, Bott N, Peremen Z, Issachar G, Laufer O, Joachim D, Jagesar R, Jongs N, Kas M, Zhuparris A, Zuiker R, Recourt K, Zuilhof Z, Cha J, Jacobs G. A Study of Novel Exploratory Tools, Digital Technologies, and Central Nervous System Biomarkers to Characterize Unipolar Depression. Frontiers in Psychiatry 2021;12 View
  12. Lee S, Kim H, Park M, Jeon H. Current Advances in Wearable Devices and Their Sensors in Patients With Depression. Frontiers in Psychiatry 2021;12 View
  13. Taliaz D, Souery D. A New Characterization of Mental Health Disorders Using Digital Behavioral Data: Evidence from Major Depressive Disorder. Journal of Clinical Medicine 2021;10(14):3109 View

Books/Policy Documents

  1. Cipriano M, Costagliola G, De Rosa M, Fuccella V, Shevchenko S. Innovation in Medicine and Healthcare. View