PCompanion – Mobiles Monitoringsystem zur Unterstützung von ParkinsonpatientenCopyright: © UKA
User-Friendly, Adaptive User Interface and Data Visualization
- 01.09.2017 to 31.01.2021
- Research Area:
- Information Design and Data Visualization
Before Parkinson's disease leads to movement impairments, there are already changes in the regulation of autonomic body functions and sleep. At present, however, there is no widely available screening and monitoring system that can provide early detection.
Challenges for the project include early detection of REM sleep disorders and changes in body functions, such as slowed movements or postural instability.
The aim of the PCompanion project was to develop the first mobile, patient-oriented screening and monitoring system for the early diagnosis and management of Parkinson's disease. The focus is on early detection of REM sleep disorders and other subthreshold changes in bodily functions, such as slowed movements or postural instability.
For the early diagnosis and management of Parkinson's disease, a personal sensor system was developed that can be used by patients and their relatives in the home environment. Data from an intuitive mobile diary application is combined with sensor data from a sleep monitoring system. Predictive algorithms evaluate the data and enable intelligent data management. Both components are embedded in a telemedical video monitoring service, where patients receive remote diagnostic support from experts. The system was developed in a user-centric way together with a large number of Parkinson's patients and their relatives in order to optimize the ergonomics and the human-machine interface.
The result of the project is a user-friendly smartphone application which, in combination with a sleep sensor system, can be used independently and easily by Parkinson's patients. The needs identified by the patients at the beginning of the project showed that they wanted to gain insight into their health data and its correlation with their behavior. Additional functions such as brain training were included in the final system through user feedback and led to a positive evaluation of the system. Controlled laboratory studies with eye-tracking led to design recommendations for an ergonomic design of the human-technical interaction as well as the data visualizations contained in the system.
The project was funded by the Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) under the funding code number 16SV7860.
|Deutsche Gesellschaft für Neurologie|
|Universitätsklinik Aachen – Neurologie|
|MVB – Medizinische Videobeobachtung GmbH|