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Applying machine learning in motor activity time series of depressed bipolar and unipolar patients compared to healthy controls." PLOS ONE 15, no. 8 (2020): e0231995."
Human Activity Recognition from Multiple Sensors Data Using Multi-fusion Representations and CNNs." ACM Transactions on Multimedia Computing, Communications, and Applications 16, no. 2 (2020): 1-19."
Heart Rate Prediction from Head Movement during Virtual Reality Treatment for Social Anxiety In 2019 International Conference on Content-Based Multimedia Indexing (CBMI). IEEE, 2019.
One-Dimensional Convolutional Neural Networks on Motor Activity Measurements in Detection of Depression In Proceedings of the 4th International Workshop on Multimedia for Personal Health & Health Care - HealthMedia '19, Edited by S. Boll, J. Lee, J. Meyer, N. Nag and N. E. O'Connor. New York, NY, USA: ACM Press, 2019.
User-adaptive models for activity and emotion recognition using deep transfer learning and data augmentation." User Modeling and User-Adapted Interaction (2019): 1-29."
Motor Activity Based Classification of Depression in Unipolar and Bipolar Patients In 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS), Edited by B. Kane. Karlstad, Sweden: IEEE, 2018.