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

Social Anxiety Disorder (SAD) (47) Special Issue on Computing and Mental Health (2018) (33) Ecological Momentary Assessment (EMA) (297)

Published on in Vol 5, No 3 (2018): Jul-Sept

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10101, first published .
Predicting Social Anxiety From Global Positioning System Traces of College Students: Feasibility Study

Predicting Social Anxiety From Global Positioning System Traces of College Students: Feasibility Study

Predicting Social Anxiety From Global Positioning System Traces of College Students: Feasibility Study

Authors of this article:

Mehdi Boukhechba1 Author Orcid Image ;   Philip Chow2 Author Orcid Image ;   Karl Fua2 Author Orcid Image ;   Bethany A Teachman2 Author Orcid Image ;   Laura E Barnes1 Author Orcid Image
Article Authors Cited by (55) Tweetations (16) Metrics

Journals

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  10. Baglione A, Gong J, Boukhechba M, Wells K, Barnes L. Leveraging Mobile Sensing to Understand and Develop Intervention Strategies to Improve Medication Adherence. IEEE Pervasive Computing 2020;19(3):24 View
  11. Rashid H, Mendu S, Daniel K, Beltzer M, Teachman B, Boukhechba M, Barnes L. Predicting Subjective Measures of Social Anxiety from Sparsely Collected Mobile Sensor Data. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(3):1 View
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  19. Mansoor H, Gerych W, Alajaji A, Buquicchio L, Chandrasekaran K, Agu E, Rundensteiner E, Rodriguez A. INPHOVIS: Interactive visual analytics for smartphone-based digital phenotyping. Visual Informatics 2023;7(2):13 View
  20. Hnoohom N, Mekruksavanich S, Jitpattanakul A. Physical Activity Recognition Based on Deep Learning Using Photoplethysmography and Wearable Inertial Sensors. Electronics 2023;12(3):693 View
  21. MacLeod L, Suruliraj B, Gall D, Bessenyei K, Hamm S, Romkey I, Bagnell A, Mattheisen M, Muthukumaraswamy V, Orji R, Meier S. A Mobile Sensing App to Monitor Youth Mental Health: Observational Pilot Study. JMIR mHealth and uHealth 2021;9(10):e20638 View
  22. Nowrouzi-Kia B, Stier J, Ayyoub L, Hutchinson L, Laframboise J, Mihailidis A. The Characteristics of Canadian University Students’ Mental Health, Engagement in Activities and Use of Smartphones: A descriptive pilot study. Health Psychology Open 2021;8(2):205510292110620 View
  23. Zarate D, Stavropoulos V, Ball M, de Sena Collier G, Jacobson N. Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence. BMC Psychiatry 2022;22(1) View
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  25. Choudhary S, Thomas N, Alshamrani S, Srinivasan G, Ellenberger J, Nawaz U, Cohen R. A Machine Learning Approach for Continuous Mining of Nonidentifiable Smartphone Data to Create a Novel Digital Biomarker Detecting Generalized Anxiety Disorder: Prospective Cohort Study. JMIR Medical Informatics 2022;10(8):e38943 View
  26. Ibrahim A, Zhang H, Clinch S, Harper S. From GPS to semantic data: how and why—a framework for enriching smartphone trajectories. Computing 2021;103(12):2763 View
  27. Jacobson N, Bhattacharya S. Digital biomarkers of anxiety disorder symptom changes: Personalized deep learning models using smartphone sensors accurately predict anxiety symptoms from ecological momentary assessments. Behaviour Research and Therapy 2022;149:104013 View
  28. Wang Z, Xiong H, Zhang J, Yang S, Boukhechba M, Zhang D, Barnes L, Dou D. From Personalized Medicine to Population Health: A Survey of mHealth Sensing Techniques. IEEE Internet of Things Journal 2022;9(17):15413 View
  29. Jiang J, Meng Q, Ji J. Combining Music and Indoor Spatial Factors Helps to Improve College Students’ Emotion During Communication. Frontiers in Psychology 2021;12 View
  30. Dong G, Tang M, Wang Z, Gao J, Guo S, Cai L, Gutierrez R, Campbel B, Barnes L, Boukhechba M. Graph Neural Networks in IoT: A Survey. ACM Transactions on Sensor Networks 2023;19(2):1 View
  31. Lee K, Lee T, Yefimova M, Kumar S, Puga F, Azuero A, Kamal A, Bakitas M, Wright A, Demiris G, Ritchie C, Pickering C, Nicholas Dionne-Odom J. Using digital phenotyping to understand health-related outcomes: A scoping review. International Journal of Medical Informatics 2023;174:105061 View
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  33. Stamatis C, Liu T, Meyerhoff J, Meng Y, Cho Y, Karr C, Curtis B, Ungar L, Mohr D. Specific associations of passively sensed smartphone data with future symptoms of avoidance, fear, and physiological distress in social anxiety. Internet Interventions 2023;34:100683 View
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Books/Policy Documents

  1. Hur J, Stockbridge M, Fox A, Shackman A. Emotion and Cognition. View
  2. Boukhechba M, Barnes L. Advances in Usability, User Experience, Wearable and Assistive Technology. View
  3. Psathas A, Papaleonidas A, Iliadis L. Computational Collective Intelligence. View
  4. Garatva P, Terhorst Y, Messner E, Karlen W, Pryss R, Baumeister H. Digital Phenotyping and Mobile Sensing. View
  5. Mansoor H, Gerych W, Alajaji A, Buquicchio L, Chandrasekaran K, Agu E, Rundensteiner E. Computer Vision, Imaging and Computer Graphics Theory and Applications. View
  6. Mondragón-González S, Burguière E, N’diaye K. Machine Learning for Brain Disorders. View