Ferreira, Denzil

The Experience Sampling Method on Mobile Devices

van Berkel, N., Ferreira, D., & Kostakos, V. (2018) · ACM Computing Surveys

Mental Health Research TopicsInnovative Human-Technology Interaction

Cited by 432

AWARE: Mobile Context Instrumentation Framework

Ferreira, D., Kostakos, V., & Dey, A. K. (2015) · Frontiers in ICT

Context-Aware Activity Recognition SystemsMobile Crowdsensing and Crowdsourcing

Cited by 409

Predicting Symptoms of Depression and Anxiety Using Smartphone and Wearable Data

Moshe, I., Terhorst, Y., Opoku Asare, K., Sander, L. B., Ferreira, D., Baumeister, H., Mohr, D. C., & Pulkki-Råback, L. (2021) · Frontiers in Psychiatry

Digital Mental Health InterventionsMental Health Research Topics

Cited by 261

Are Smartphones Ubiquitous?: An in-depth survey of smartphone adoption by seniors

Berenguer, A., Goncalves, J., Hosio, S., Ferreira, D., Anagnostopoulos, T., & Kostakos, V. (2017) · IEEE Consumer Electronics Magazine

Technology Use by Older AdultsTechnology Adoption and User Behaviour

Cited by 150

Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study

Opoku Asare, K., Terhorst, Y., Vega, J., Peltonen, E., Lagerspetz, E., & Ferreira, D. (2021) · JMIR mHealth and uHealth

Digital Mental Health InterventionsEmotion and Mood Recognition

Cited by 145

Predicting interruptibility for manual data collection: a cluster-based user model

Visuri, A., van Berkel, N., Luo, C., Goncalves, J., Ferreira, D., & Kostakos, V. (2017) · Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services

Innovative Human-Technology InteractionPersonal Information Management and User Behavior

Cited by 28

Towards early detection of depression through smartphone sensing

Opoku Asare, K., Visuri, A., & Ferreira, D. S. T. (2019) · Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers

Emotion and Mood RecognitionDigital Mental Health Interventions

Cited by 24