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Updated: Jun 6, 2026

Bringing the Clinic Home: An At-Home Multi-Modal Data Collection Ecosystem to Support Adaptive Deep Brain Stimulation
Published on: July 14, 2023
Home-based monitoring and assessment of Parkinson's disease
L Cunningham1, S Mason, C Nugent
1Faculty of Computing and Engineering, Computer Science Research Instituteand School of Computing and Mathematics, University of Ulster, Northern Ireland, BT37 0QB, UK. cunningham-l5@email.ulster.ac.uk
Abstract:
As a clinically complex neurodegenerative disease, Parkinson's disease (PD) requires regular assessment and close monitoring. In our current study, we have developed a home-based tool designed to monitor and assess peripheral motor symptoms. An evaluation of the tool was carried out over a period of ten weeks on ten people with idiopathic PD. Participants were asked to use the tool twice daily over four days, once when their medication was working at its best ("on" state) and once when it had worn off ("off" state). Results showed the ability of the data collected to distinguish the "on" and "off" state and also demonstrated statistically significant differences in timed assessments. It is anticipated that this tool could be used in the home environment as an early alert to a change in clinical condition or to monitor the effects of changes in prescribed medications used to manage PD.
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