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

Depression and Mood Disorders; Suicide Prevention (1392) Digital Biomarkers and Digital Phenotyping (198) Ecological Momentary Assessment (EMA) (321) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1428) Wearable Devices and Sensors (903)

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

Authors of this article:

Francesca Cormack1, 2 Author Orcid Image ;   Maggie McCue3 Author Orcid Image ;   Nick Taptiklis1, 2 Author Orcid Image ;   Caroline Skirrow1, 4 Author Orcid Image ;   Emilie Glazer2, 5 Author Orcid Image ;   Elli Panagopoulos2, 5 Author Orcid Image ;   Tempest A van Schaik2, 5 Author Orcid Image ;   Ben Fehnert2, 5 Author Orcid Image ;   James King2, 5 Author Orcid Image ;   Jennifer H Barnett1, 2, 6 Author Orcid Image
Article Authors Cited by (43) Tweetations (38) Metrics

Journals

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  20. Mughal H, Javed A, Rizwan M, Almadhor A, Kryvinska N. Parkinson’s Disease Management via Wearable Sensors: A Systematic Review. IEEE Access 2022;10:35219 View
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  23. Jeng M, Pai F, Yeh T. Antecedents for Older Adults’ Intention to Use Smart Health Wearable Devices-Technology Anxiety as a Moderator. Behavioral Sciences 2022;12(4):114 View
  24. de-la-Fuente-Robles Y, Ricoy-Cano A, Albín-Rodríguez A, López-Ruiz J, Espinilla-Estévez M. Past, Present and Future of Research on Wearable Technologies for Healthcare: A Bibliometric Analysis Using Scopus. Sensors 2022;22(22):8599 View
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  27. Lui G, Loughnane D, Polley C, Jayarathna T, Breen P. The Apple Watch for Monitoring Mental Health–Related Physiological Symptoms: Literature Review. JMIR Mental Health 2022;9(9):e37354 View
  28. Goodday S, Karlin E, Brooks A, Chapman C, Karlin D, Foschini L, Kipping E, Wildman M, Francis M, Greenman H, Li L, Schadt E, Ghassemi M, Goldenberg A, Cormack F, Taptiklis N, Centen C, Smith S, Friend S. Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum. npj Digital Medicine 2022;5(1) View
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  30. Curcic J, Vallejo V, Sorinas J, Sverdlov O, Praestgaard J, Piksa M, Deurinck M, Erdemli G, Bügler M, Tarnanas I, Taptiklis N, Cormack F, Anker R, Massé F, Souillard-Mandar W, Intrator N, Molcho L, Madero E, Bott N, Chambers M, Tamory J, Shulz M, Fernandez G, Simpson W, Robin J, Snædal J, Cha J, Hannesdottir K. Description of the Method for Evaluating Digital Endpoints in Alzheimer Disease Study: Protocol for an Exploratory, Cross-sectional Study. JMIR Research Protocols 2022;11(8):e35442 View
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  32. Jenciūtė G, Kasputytė G, Bunevičienė I, Korobeinikova E, Vaitiekus D, Inčiūra A, Jaruševičius L, Bunevičius R, Krikštolaitis R, Krilavičius T, Juozaitytė E, Bunevičius A. Digital Phenotyping for Monitoring and Disease Trajectory Prediction of Patients With Cancer: Protocol for a Prospective Observational Cohort Study. JMIR Research Protocols 2023;12:e49096 View
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  35. Cormack F, McCue M, Skirrow C, Cashdollar N, Taptiklis N, van Schaik T, Fehnert B, King J, Chrones L, Sarkey S, Kroll J, Barnett J. Characterizing Longitudinal Patterns in Cognition, Mood, And Activity in Depression With 6-Week High-Frequency Wearable Assessment: Observational Study. JMIR Mental Health 2024;11:e46895 View
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Books/Policy Documents

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