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Mobile-based Monitoring of Parkinson's Disease., , , , , , , and . MUM, page 441-448. ACM, (2018)Mood ratings and digital biomarkers from smartphone and wearable data differentiates and predicts depression status: A longitudinal data analysis., , , , , , , and . Pervasive Mob. Comput., (2022)Wild by Design: Workshop on Designing Ubiquitous Health Monitoring Technologies for Challenging Environments., , , , , , , , , and 1 other author(s). UbiComp/ISWC Adjunct, page 508-510. ACM, (2021)Back to Analogue: Self-Reporting for Parkinson's Disease., , , , , , , and . CHI, page 74. ACM, (2018)Exploratory machine learning modeling of adaptive and maladaptive personality traits from passively sensed behavior., , , , , , , , and . Future Gener. Comput. Syst., (2022)Robot Evolutionary Localization Based on Attentive Visual Short-Term Memory., , and . Sensors, 13 (1): 1268-1299 (2013)Challenges of Parkinson's Disease: User Experiences with STOP., , , , , , , and . MobileHCI, page 22:1-22:11. ACM, (2019)Using web interaction to monitor parkinson's disease progression through behavioural inferences on the web.. W4A, page 36:1-36:3. ACM, (2016)Exploring Perceptions of Cross-Sectoral Data Sharing with People with Parkinson's., , , , , , , , , and . CHI, page 280:1-280:14. ACM, (2022)Me in the Wild: An Exploratory Study Using Smartphones to Detect the Onset of Depression., , , and . MobiHealth, volume 440 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 121-145. Springer, (2021)