Title:
Assessment and modulation of essential tremor using peripheral-nerve stimulation
Assessment and modulation of essential tremor using peripheral-nerve stimulation
Author(s)
Kim, Jeonghee
Advisor(s)
DeWeerth, Stephen P.
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Abstract
Tremor is an abnormal oscillatory movement, observed in patients with essential tremor (ET), Parkinson’s Disease, and other neurological disorders. ET obstructs patient’s movements that require high degrees of dexterity and precision, resulting in a reduction of the quality of life for the patient. Current quantification methods of ET, which typically rely on subjective ratings by trained clinicians or researchers, are potentially susceptible to inter- and intra-rater variability. Most treatments for reducing tremors, such as medications and thalamic deep brain stimulation, have not been adopted broadly because of the invasiveness of the treatments and their lack of efficacy. To address these limitations, the objectives of this PhD dissertation are (1) to quantitatively assess tremor movement, and (2) to modulate/attenuate tremor movement by adjusting the parameters of electrical stimulation on peripheral nerves using a custom-designed real-time system. I have developed (1) an automatic and quantitative method consisting of three computer-based tasks along with their performance metrics that assess the characteristics of tremor, and (2) a wireless tremor modulation system via peripheral-nerve electrical stimulation using a wearable wrist device. I analyzed that the performance metrics of the proposed computer-based assessment tasks were highly correlated with tremor frequency and power. I found that peripheral-nerve stimulation significantly reduced the tremor frequency and tremor power, and the subject with stronger tremor exhibited a greater reduction in tremor power. I examined the effects of the stimulation parameters (stimulation amplitude, frequency, duty cycle, phase, and stimulation sites), and found that the proper range of stimulation amplitudes varied according to current tremor status. In a future study, I plan to develop a closed-loop optimization algorithm based on tremor characteristics of each patient to maximize the effect of stimulation in tremor modulation.
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Date Issued
2018-01-11
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Dissertation