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

Mobile Health (mhealth) (2765) mHealth for Wellness, Behavior Change and Prevention (2743) Wearable Devices and Sensors (818) Insomnia and Sleep Hygiene (151) Special Issue Computing and Mental Health 2016/17 (Guest Editors: Calvo, Dinakar, Torous, Picard, Christensen) (22)

Published on in Vol 19, No 4 (2017): April

Scalable Passive Sleep Monitoring Using Mobile Phones: Opportunities and Obstacles

Scalable Passive Sleep Monitoring Using Mobile Phones: Opportunities and Obstacles

Scalable Passive Sleep Monitoring Using Mobile Phones: Opportunities and Obstacles

Authors of this article:

Sohrab Saeb1 Author Orcid Image ;   Thaddeus R Cybulski2 Author Orcid Image ;   Stephen M Schueller1 Author Orcid Image ;   Konrad P Kording2 Author Orcid Image ;   David C Mohr1 Author Orcid Image
Article Authors Cited by (29) Tweetations (34) Metrics

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  17. Adler D, Tseng E, Moon K, Young J, Kane J, Moss E, Mohr D, Choudhury T. Burnout and the Quantified Workplace: Tensions around Personal Sensing Interventions for Stress in Resident Physicians. Proceedings of the ACM on Human-Computer Interaction 2022;6(CSCW2):1 View
  18. Niemeijer K, Mestdagh M, Kuppens P. Tracking Subjective Sleep Quality and Mood With Mobile Sensing: Multiverse Study. Journal of Medical Internet Research 2022;24(3):e25643 View
  19. Frank E, Wallace M, Matthews M, Kendrick J, Leach J, Moore T, Aranovich G, Choudhury T, Shah N, Framroze Z, Posey G, Burgess S, Kupfer D. Personalized digital intervention for depression based on social rhythm principles adds significantly to outpatient treatment. Frontiers in Digital Health 2022;4 View
  20. Jalali N, Sahu K, Oetomo A, Morita P. Usability of Smart Home Thermostat to Evaluate the Impact of Weekdays and Seasons on Sleep Patterns and Indoor Stay: Observational Study. JMIR mHealth and uHealth 2022;10(4):e28811 View
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Books/Policy Documents

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