An adaptable phase-tracking system for Parkinsonian rest tremor: design and in-clinic feasibility
Author(s)
Type
Journal Article
Abstract
Background: Tremor is the most common movement disorder and a prevalent symptom of neurodegenerative conditions such as Parkinson’s disease (PD). Given the limitations of medication, which may not effectively treat tremor, and the limited availability of surgical treatments such as deep brain stimulation, there is a pressing clinical need for non-invasive therapeutic alternatives, including peripheral electrical stimulation. The high variability of PD tremor poses a challenge to such therapies and calls for person-specific stimulation parameters. Methods: We developed a wrist-worn system incorporating an adaptable phase-tracking algorithm designed for real-time estimation of Parkinsonian rest tremor phase. The algorithm dynamically adapts to tremor variability, including changes in the axis of maximum excursion and center frequency. The system was first validated offline, followed by in-clinic feasibility testing in three individuals with PD. The system triggered the delivery of both phasic and open-loop electrical stimulation to the participant’s wrist. Results: Robust phase estimation was achieved both offline and in all participants. The system adapted to changes in tremor dominant axis and center frequency. Modest tremor modulation was observed at select person-specific settings. Conclusion: This work provides a novel platform for research involving tremor phase tracking, accounting for PD tremor variability, and a foundation for developing personalized, non-invasive tremor management strategies. Clinical and Translational Impact Statement—This study presents a wearable system for adaptive tremor phase tracking validated in individuals with Parkinson’s disease and establishes a foundation for further development of personalized non-invasive tremor management strategies. Category: Clinical Research
Date Issued
2025-10-24
Date Acceptance
2025-10-15
Citation
IEEE Journal of Translational Engineering in Health and Medicine, 2025, 13, pp.507-516
ISSN
2168-2372
Publisher
IEEE
Start Page
507
End Page
516
Journal / Book Title
IEEE Journal of Translational Engineering in Health and Medicine
Volume
13
Copyright Statement
© 2025 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
License URL
Publication Status
Published
Date Publish Online
2025-10-24