Parkinson's Disease Publications
Parkinson’s Disease Research
Publications related to Parkinson’s Disease research, including passive social sensing, smartphone-based monitoring, and digital phenotyping.
7 publications | ← Back to all publications
2020
Kuosmanen, E. et al. (2020). “Smartphone-Based Monitoring of Parkinson Disease: Quasi-Experimental Study to Quantify Hand Tremor Severity and Medication Effectiveness”. JMIR mHealth and uHealth, 8(11), e21543. DOI: 10.2196/21543.
Kuosmanen, E. et al. (2020). “Smartphone-Based Monitoring of Parkinson Disease: Quasi-Experimental Study to Quantify Hand Tremor Severity and Medication Effectiveness (Preprint)”. DOI: 10.2196/preprints.21543.
Zhang, H. et al. (2020). “Passive Social Sensing with Smartphone: A Systematic Review (Preprint)”. DOI: 10.2196/preprints.20539.
2019
Kuosmanen, E. et al. (2019). “Challenges of Parkinson’s Disease”. MobileHCI ‘19: Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services. DOI: 10.1145/3338286.3340133.
2018
Kuosmanen, E. et al. (2018). “Mobile-based Monitoring of Parkinson’”. MUM 2018 - 17th International Conference on Mobile and Ubiquitous Multimedia, Proceedings, pp. 441–448. DOI: 10.1145/3282894.3289737.
Vega, J. et al. (2018). “Back to analogue: Self-reporting for Parkinson’s Disease”. CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems, pp. 1–13. DOI: 10.1145/3173574.3173648.
2017
Vega, J. et al. (2017). “Unobtrusive Monitoring of Parkinson’s Disease Based on Digital Biomarkers of Human Behaviour”. DOI: 10.1145/3132525.3134782.
Research Themes
Passive Social Sensing
Using smartphone data to understand social behaviour patterns in people with Parkinson’s disease.
Digital Phenotyping
Leveraging smartphone sensors to monitor symptoms and medication effectiveness without requiring active user input.
Smartphone-Based Monitoring
Developing unobtrusive methods to track tremor, gait, and other motor symptoms through everyday smartphone use.