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Characterizing the Power Spectral Density of Essential Tremor

Year: 2023

Presenter Name: Noah Francom

Tremor is the most common movement disorder, and current treatment options are not satisfactory to many patients [1,2]. Whether tremor is caused by out-of-phase activity in a pair of antagonist muscles or by rhythmic activity in a single agonist is unknown. To answer this question, we first had to characterize the spectral distribution of tremor power within the tremor band (4-8 Hz). The purpose of our research is to characterize the shape of tremor within the tremor band to better understand the muscle activity that causes tremor using experimental data from Essential Tremor patients. Methods
Surface electromyography (sEMG) signals were recently collected by Pigg et al. from the 15 major superficial muscles of the upper limb in 25 Essential Tremor patients as they held various postures representing common activities [3]. We calculated the power spectral density of each muscle's sEMG in each posture using Matlab's pwelch function. From these power spectral densities, we identified the most prominent peaks, determined their widths, and integrated over those widths to determine what percentage of tremor-band power was contained within the peaks. We identified for each instance the number of peaks, the width of each peak, the percentage of power contained in each peak, and the total percentage of tremor band power contained in all the peaks. Results and Discussion
The initial findings show that patients with severe tremor tend to have distinct peaks within the tremor band. Patients with less severe tremor have a greater number of instances where significant peaks are present in the tremor band. Many factors could cause this, one being that the power spectra of patients with less severe tremor tends to be of a broad-band nature. This suggests that tremor stems from a high concentration of muscular power at a frequency within the range of 4-8 Hz. Significance
This research aims to determine the spectral distribution of tremor in patients with Essential Tremor. From this characterization, we can analyze the power and phase differences between muscles. To determine the mechanical source of tremor, we can then find to what extent tremorogenic activity is represented by significant out of phase tremor-band activity in antagonist muscles verses significant tremor-band activity in only one muscle. Understanding the source of tremor will allow us to better identify which muscles are most responsible for it and therefore where is best to intervene with tremor suppression techniques. Acknowledgements
This research was supported by NIH grant R15 NS087447-02. References
[1] Bhatia, K. P., et al. 2018. Mov. Disord., 33(1).
[2] Anouti, A., et al. 1995. West. J. Med., 162(6)
[3] Pigg, A. C., et al. 2020. Clin. Neurophysiol., 131.
University / Institution: Brigham Young University
Type: Poster
Format: In Person
Presentation #B24
SESSION B (10:45AM-12:15PM)
Area of Research: Engineering
Faculty Mentor: Steven Charles