Technological Support for Parkinson’s Disease Patients’ Self-Care
Thesis event information
Date and time of the thesis defence
Place of the thesis defence
L10, Linnanmaa
Topic of the dissertation
Technological Support for Parkinson’s Disease Patients’ Self-Care
Doctoral candidate
Master of Science Elina Kuosmanen
Faculty and unit
University of Oulu Graduate School, Faculty of Information Technology and Electrical Engineering, The Center for Ubiquitous Computing
Subject of study
Computer Science
Opponent
Professor Cecilia Mascolo, University of Cambridge
Custos
Docent Denzil Ferreira, University of Oulu
Technological Support for Parkinson’s Disease Patients’ Self-Care
Parkinson’s disease (PD) is an incurable neurodegenerative disorder. PD manifests various symptoms, such as tremors, stiffness and slowness, and the symptoms impact have a significant impact on patients’ life. Self-care is an essential part of living with a chronic condition. Self-care refers to all actions that aim to minimise the disease’s impact on daily life. The objective of this thesis was to create new applications for supporting PD self-care.
First, we implemented a mobile application, STOP, to enable patients’ self-assessment and aid in medication adherence. We demonstrate that accelerometer data from STOP are useful for tremor and medication effect detection. We found the drawing performance in digital drawing tasks differed with PD patients and age matching controls. We found PD patients receptive to digital tools to track their medication intake and symptoms. The possibility of sharing the data with medical personnel to improve and assist their own care would motivate the use of digital tools.
As a second application, we collected and assessed community-contributed self-care techniques, and established and evaluated an open online repository, the PDCareBox, for PD self-care practice data. The peer-provided data is actionable and understandable, and in a daily life context, supplementing clinical information of PD. The PDCareBox provides an organised way to share and discover the knowledge gained by the experience of living with PD.
First, we implemented a mobile application, STOP, to enable patients’ self-assessment and aid in medication adherence. We demonstrate that accelerometer data from STOP are useful for tremor and medication effect detection. We found the drawing performance in digital drawing tasks differed with PD patients and age matching controls. We found PD patients receptive to digital tools to track their medication intake and symptoms. The possibility of sharing the data with medical personnel to improve and assist their own care would motivate the use of digital tools.
As a second application, we collected and assessed community-contributed self-care techniques, and established and evaluated an open online repository, the PDCareBox, for PD self-care practice data. The peer-provided data is actionable and understandable, and in a daily life context, supplementing clinical information of PD. The PDCareBox provides an organised way to share and discover the knowledge gained by the experience of living with PD.
Last updated: 23.1.2024