A Frequency Domain Based Approach to Evaluating Manual Tracking Behavior in Parkinsons Disease

by Gabriel A Parras

Institution: University of New Mexico
Year: 2017
Keywords: Manual Tracking; Parkinson's Disease; Galvanic Vestibular Stimulation; GVS; Electrical and Computer Engineering
Posted: 02/01/2018
Record ID: 2154866
Full text PDF: http://digitalrepository.unm.edu/ece_etds/345


Parkinsons disease (PD) is characterized in part by its neurodegenerative effects, which include bradykinesia, tremor, rigidity, and many other symptoms. While treatments such as Levodopa and deep brain stimulation are available, they both have associated complications. Galvanic vestibular stimulation (GVS) is a non-invasive method used to stimulate the vestibular nerves with electric current and it has shown promise as a possible treatment for patients with PD. In order to assess the efficacy of GVS, I examined data collected from a manual pursuit tracking experiment. The experiment involved ten patients with varying severities of PD who were asked to perform a series of eight 90 second tasks both before and after receiving a dose of fast acting Levodopa. The patients unknowingly received GVS below sensory threshold for four of the tasks. They were asked to track a vertically oscillating target on a screen by using a joystick to move a cursor next to the target. I applied Welchs power spectral density method to determine the power of high frequency noise associated with sub-movement induced error in patients tracking signal. I then paired trials where patients received GVS with trials where they did not. These pairs were normalized by adding the input signal to the output signal of the other trial in the pair. The results of a paired t-test determined there was a statistically significant (p < 0.05) improvement in performance when GVS was applied in the trails that occurred after Levodopa was administered. The results suggest there are some synergistic effects between Levodopa and GVS. More research is needed to determine if GVS can provide statistically significant increases in performance minus the apparent synergistic effects. Advisors/Committee Members: Dr. Meeko Oishi, Dr. Rafael Fierro, Dr. Marios Pattichis.