Campbell, Andrew T.

A survey of mobile phone sensing

Lane, N., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., & Campbell, A. (2010) · IEEE Communications Magazine

Mobile Crowdsensing and CrowdsourcingContext-Aware Activity Recognition Systems

Cited by 2,292

StudentLife: assessing mental health, academic performance and behavioral trends of college students using smartphones

Wang, R., Chen, F., Chen, Z., Li, T., Harari, G., Tignor, S., Zhou, X., Ben-Zeev, D., & Campbell, A. T. (2014) · Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Digital Mental Health InterventionsStudent Stress and Coping

Cited by 1,116

Mental Health and Behavior of College Students During the Early Phases of the COVID-19 Pandemic: Longitudinal Smartphone and Ecological Momentary Assessment Study

Huckins, J. F., daSilva, A. W., Wang, W., Hedlund, E., Rogers, C., Nepal, S. K., Wu, J., Obuchi, M., Murphy, E. I., Meyer, M. L., et al. (2020) · Journal of Medical Internet Research

COVID-19 and Mental HealthDigital Mental Health Interventions

Cited by 759

Using Smartphones to Collect Behavioral Data in Psychological Science: Opportunities, Practical Considerations, and Challenges

Harari, G. M., Lane, N. D., Wang, R., Crosier, B. S., Campbell, A. T., & Gosling, S. D. (2016) · Perspectives on Psychological Science

Human Mobility and Location-Based AnalysisMobile Crowdsensing and Crowdsourcing

Cited by 515

Next-generation psychiatric assessment: Using smartphone sensors to monitor behavior and mental health.

Ben-Zeev, D., Scherer, E. A., Wang, R., Xie, H., & Campbell, A. T. (2015) · Psychiatric Rehabilitation Journal

Mental Health Research TopicsDigital Mental Health Interventions

Cited by 429

BeWell: A Smartphone Application to Monitor, Model and Promote Wellbeing

Lane, N., Mohammod, M., Lin, M., Yang, X., Lu, H., Ali, S., Doryab, A., Berke, E., Choudhury, T., & Campbell, A. (2011) · Proceedings of the 5th International ICST Conference on Pervasive Computing Technologies for Healthcare

Mobile Health and mHealth ApplicationsDigital Mental Health Interventions

Cited by 409

Tracking Depression Dynamics in College Students Using Mobile Phone and Wearable Sensing

Wang, R., Wang, W., daSilva, A., Huckins, J. F., Kelley, W. M., Heatherton, T. F., & Campbell, A. T. (2018) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Digital Mental Health InterventionsMental Health Research Topics

Cited by 340

CrossCheck: toward passive sensing and detection of mental health changes in people with schizophrenia

Wang, R., Aung, M. S. H., Abdullah, S., Brian, R., Campbell, A. T., Choudhury, T., Hauser, M., Kane, J., Merrill, M., Scherer, E. A., et al. (2016) · Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Digital Mental Health InterventionsMental Health Research Topics

Cited by 257

Enabling large-scale human activity inference on smartphones using community similarity networks (csn)

Lane, N. D., Xu, Y., Lu, H., Hu, S., Choudhury, T., Campbell, A. T., & Zhao, F. (2011) · Proceedings of the 13th international conference on Ubiquitous computing

Context-Aware Activity Recognition SystemsHuman Mobility and Location-Based Analysis

Cited by 171

Sensing Behavioral Change over Time: Using Within-Person Variability Features from Mobile Sensing to Predict Personality Traits

Wang, W., Harari, G. M., Wang, R., Müller, S. R., Mirjafari, S., Masaba, K., & Campbell, A. T. (2018) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Human Mobility and Location-Based AnalysisContext-Aware Activity Recognition Systems

Cited by 100

GLOBEM: Cross-Dataset Generalization of Longitudinal Human Behavior Modeling

Xu, X., Liu, X., Zhang, H., Wang, W., Nepal, S., Sefidgar, Y., Seo, W., Kuehn, K. S., Huckins, J. F., Morris, M. E., et al. (2022) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Emotion and Mood RecognitionContext-Aware Activity Recognition Systems

Cited by 96

Fusing Mobile Phone Sensing and Brain Imaging to Assess Depression in College Students

Huckins, J. F., daSilva, A. W., Wang, R., Wang, W., Hedlund, E. L., Murphy, E. I., Lopez, R. B., Rogers, C., Holtzheimer, P. E., Kelley, W. M., et al. (2019) · Frontiers in Neuroscience

Functional Brain Connectivity StudiesMental Health Research Topics

Cited by 51

Using behavioral rhythms and multi-task learning to predict fine-grained symptoms of schizophrenia

Tseng, V. W.-S., Sano, A., Ben-Zeev, D., Brian, R., Campbell, A. T., Hauser, M., Kane, J. M., Scherer, E. A., Wang, R., Wang, W., et al. (2020) · Scientific Reports

Mental Health Research TopicsDigital Mental Health Interventions

Cited by 44

Predicting Brain Functional Connectivity Using Mobile Sensing

Obuchi, M., Huckins, J. F., Wang, W., daSilva, A., Rogers, C., Murphy, E., Hedlund, E., Holtzheimer, P., Mirjafari, S., & Campbell, A. (2020) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Functional Brain Connectivity StudiesMental Health Research Topics

Cited by 29

The power of speech in the wild: discriminative power of daily voice diaries in understanding auditory verbal hallucinations using deep learning

Wang, W., Xu, W., Chander, A., Nepal, S., Buck, B., Pakhomov, S., Cohen, T., Ben-Zeev, D., & Campbell, A. (2023) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Emotion and Mood RecognitionMental Health Research Topics

Cited by 19