IBM computer usability satisfaction questionnaires: psychometric evaluation and instructions for use
International Journal of Human-Computer Interaction
Past, present, and future of decision support technology
Decision Support Systems - Special issue: Decision support systems: Directions for the next decade
Engineering Web Applications
Monitoring motor fluctuations in patients with Parkinson's disease using wearable sensors
IEEE Transactions on Information Technology in Biomedicine - Special section on body sensor networks
A home environment test battery for status assessment in patients with advanced Parkinson's disease
Computer Methods and Programs in Biomedicine
User-centred design of a mobile self-management solution for Parkinson's disease
Proceedings of the 12th International Conference on Mobile and Ubiquitous Multimedia
A computer vision framework for finger-tapping evaluation in Parkinson's disease
Artificial Intelligence in Medicine
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This paper describes a web-based system for enabling remote monitoring of patients with Parkinson's disease (PD) and supporting clinicians in treating their patients. The system consists of a patient node for subjective and objective data collection based on a handheld computer, a service node for data storage and processing, and a web application for data presentation. Using statistical and machine learning methods, time series of raw data are summarized into scores for conceptual symptom dimensions and an ''overall test score'' providing a comprehensive profile of patient's health during a test period of about one week. The handheld unit was used quarterly or biannually by 65 patients with advanced PD for up to four years at nine clinics in Sweden. The IBM Computer System Usability Questionnaire was administered to assess nurses' satisfaction with the web application. Results showed that a majority of the nurses were quite satisfied with the usability although a sizeable minority were not. Our findings support that this system can become an efficient tool to easily access relevant symptom information from the home environment of PD patients.