Published on 18.04.17 in Vol 19, No 4 (2017): April
Works citing "Scalable Passive Sleep Monitoring Using Mobile Phones: Opportunities and Obstacles"
According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.6821):
(note that this is only a small subset of citations)
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Burgdorf A, Güthe I, Jovanović M, Kutafina E, Kohlschein C, Bitsch J, Jonas SM. The mobile sleep lab app: An open-source framework for mobile sleep assessment based on consumer-grade wearable devices. Computers in Biology and Medicine 2018;103:8
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Hossain HMS, Ramamurthy SR, Khan MAAH, Roy N. An Active Sleep Monitoring Framework Using Wearables. ACM Transactions on Interactive Intelligent Systems 2018;8(3):1
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. Using technology to improve patient care. Medical Journal of Australia 2020;212(6):254
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Trifan A, Oliveira M, Oliveira JL. Passive Sensing of Health Outcomes Through Smartphones: Systematic Review of Current Solutions and Possible Limitations. JMIR mHealth and uHealth 2019;7(8):e12649
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Turvey C, Fortney J. The Use of Telemedicine and Mobile Technology to Promote Population Health and Population Management for Psychiatric Disorders. Current Psychiatry Reports 2017;19(11)
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Calvo RA, Dinakar K, Picard R, Christensen H, Torous J. Toward Impactful Collaborations on Computing and Mental Health. Journal of Medical Internet Research 2018;20(2):e49
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Aledavood T, Torous J, Triana Hoyos AM, Naslund JA, Onnela J, Keshavan M. Smartphone-Based Tracking of Sleep in Depression, Anxiety, and Psychotic Disorders. Current Psychiatry Reports 2019;21(7)
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Snyder C, Dorsey E, Atreja A. The Best Digital Biomarkers Papers of 2017. Digital Biomarkers 2018;2(2):64
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Nicholas J, Shilton K, Schueller SM, Gray EL, Kwasny MJ, Mohr DC. The Role of Data Type and Recipient in Individuals’ Perspectives on Sharing Passively Collected Smartphone Data for Mental Health: Cross-Sectional Questionnaire Study. JMIR mHealth and uHealth 2019;7(4):e12578
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Purswani JM, Dicker AP, Champ CE, Cantor M, Ohri N. Big Data From Small Devices: The Future of Smartphones in Oncology. Seminars in Radiation Oncology 2019;29(4):338
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Sano A, Chen W, Lopez-Martinez D, Taylor S, Picard RW. Multimodal Ambulatory Sleep Detection Using LSTM Recurrent Neural Networks. IEEE Journal of Biomedical and Health Informatics 2019;23(4):1607
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Azimi I, Oti O, Labbaf S, Niela-Vilen H, Axelin A, Dutt N, Liljeberg P, Rahmani AM. Personalized Maternal Sleep Quality Assessment: An Objective IoT-based Longitudinal Study. IEEE Access 2019;7:93433
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Thong MSY, Chan RJ, van den Hurk C, Fessele K, Tan W, Poprawski D, Fernández-Ortega P, Paterson C, Fitch MI. Going beyond (electronic) patient-reported outcomes: harnessing the benefits of smart technology and ecological momentary assessment in cancer survivorship research. Supportive Care in Cancer 2021;29(1):7
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Baniasadi T, Niakan Kalhori SR, Ayyoubzadeh SM, Zakerabasali S, Pourmohamadkhan M. Study of challenges to utilise mobile-based health care monitoring systems: A descriptive literature review. Journal of Telemedicine and Telecare 2018;24(10):661
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Kim J, Kim T, Shin J, Choe G, Lim HJ, Rhee C, Lee K, Cho S. Prediction of Obstructive Sleep Apnea Based on Respiratory Sounds Recorded Between Sleep Onset and Sleep Offset. Clinical and Experimental Otorhinolaryngology 2019;12(1):72
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Zhou L, DeAlmeida D, Parmanto B. Applying a User-Centered Approach to Building a Mobile Personal Health Record App: Development and Usability Study. JMIR mHealth and uHealth 2019;7(7):e13194
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Adler DA, Tseng E, Moon KC, Young JQ, Kane JM, Moss E, Mohr DC, 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
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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
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Frank E, Wallace ML, Matthews MJ, Kendrick J, Leach J, Moore T, Aranovich G, Choudhury T, Shah NR, Framroze Z, Posey G, Burgess SA, Kupfer DJ. Personalized digital intervention for depression based on social rhythm principles adds significantly to outpatient treatment. Frontiers in Digital Health 2022;4
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Jalali N, Sahu KS, Oetomo A, Morita PP. 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
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Gopalakrishnan A, Venkataraman R, Gururajan R, Zhou X, Genrich R. Mobile phone enabled mental health monitoring to enhance diagnosis for severity assessment of behaviours: a review. PeerJ Computer Science 2022;8:e1042
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Smolders K, Druijff-van de Woestijne G, Meijer K, Mcconchie H, de Kort Y. Smartphone Keyboard Interaction Monitoring as an Unobtrusive Method to Approximate Rest-Activity Patterns: Experience Sampling Study Investigating Interindividual and Metric-Specific Variations. Journal of Medical Internet Research 2023;25:e38066
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Al-Saedi AA, Boeva V, Casalicchio E, Exner P. Context-Aware Edge-Based AI Models for Wireless Sensor Networks—An Overview. Sensors 2022;22(15):5544
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She X, Zhai Y, Henao R, Woods CW, Chiu C, Ginsburg GS, Song PXK, Hero AO. Adaptive Multi-Channel Event Segmentation and Feature Extraction for Monitoring Health Outcomes. IEEE Transactions on Biomedical Engineering 2021;68(8):2377
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Langholm C, Byun AJS, Mullington J, Torous J. Monitoring sleep using smartphone data in a population of college students. npj Mental Health Research 2023;2(1)
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.6821):
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Krajchevska E, Petreska N, Handjiski O, Andovska S, Ilijoski B, Lameski P, Ribarski P, Tojtovska B. ICT Innovations 2021. Digital Transformation. 2022. Chapter 15:198
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