Analyzing the Effects of Parameters for Tremor Modulation via Phase-Locked Electrical Stimulation on a Peripheral Nerveopen access
- Authors
- Kim, Jeonghee; Wichmann, Thomas; Inan, Omer T; DeWeerth, Stephen P
- Issue Date
- Jan-2022
- Publisher
- MDPI
- Keywords
- essential tremor; peripheral nerve stimulation; neuromodulation; parameter optimization; tremor quantification; wearable non-invasive stimulation
- Citation
- JOURNAL OF PERSONALIZED MEDICINE, v.12, no.1, pp.1 - 15
- Indexed
- SCIE
SCOPUS
- Journal Title
- JOURNAL OF PERSONALIZED MEDICINE
- Volume
- 12
- Number
- 1
- Start Page
- 1
- End Page
- 15
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/187303
- DOI
- 10.3390/jpm12010076
- ISSN
- 2075-4426
- Abstract
- (1) Background: Non-invasive neuromodulation is a promising alternative to medication or deep-brain stimulation treatment for Parkinson's Disease or essential tremor. In previous work, we developed and tested a wearable system that modulates tremor via the non-invasive, electrical stimulation of peripheral nerves. In this article, we examine the proper range and the effects of various stimulation parameters for phase-locked stimulation. (2) Methods: We recruited nine participants with essential tremor. The subjects performed a bean-transfer task that mimics an eating activity to elicit kinetic tremor while using the wearable stimulation system. We examined the effects of stimulation with a fixed duty cycle, at different stimulation amplitudes and frequencies. The epochs of stimulation were locked to one of four phase positions of ongoing tremor, as measured with an accelerometer. We analyzed stimulation-evoked changes of the frequency and amplitude of tremor. (3) Results: We found that the higher tremor amplitude group experienced a higher rate of tremor power reduction (up to 65%) with a higher amplitude of stimulation when the stimulation was applied at the +/- peak of tremor phase. (4) Conclusions: The stimulation parameter can be adjusted to optimize tremor reduction, and this study lays the foundation for future large-scale parameter optimization experiments for personalized peripheral nerve stimulation.
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