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- Genre: Doctoral Dissertation
Description
Stroke is the leading cause of long-term disability in the U.S., with up to 60% of strokescausing speech loss. Individuals with severe stroke, who require the most frequent, intense speech therapy, often cannot adhere to treatments due to high cost and low success rates. Therefore, the ability to make functionally significant changes in individuals with severe post- stroke aphasia remains a key challenge for the rehabilitation community. This dissertation aimed to evaluate the efficacy of Startle Adjuvant Rehabilitation Therapy (START), a tele-enabled, low- cost treatment, to improve quality of life and speech in individuals with severe-to-moderate stroke. START is the exposure to startling acoustic stimuli during practice of motor tasks in individuals with stroke. START increases the speed and intensity of practice in severely impaired post-stroke reaching, with START eliciting muscle activity 2-3 times higher than maximum voluntary contraction. Voluntary reaching distance, onset, and final accuracy increased after a session of START, suggesting a rehabilitative effect. However, START has not been evaluated during impaired speech. The objective of this study is to determine if impaired speech can be elicited by startling acoustic stimuli, and if three days of START training can enhance clinical measures of moderate to severe post-stroke aphasia and apraxia of speech. This dissertation evaluates START in 42 individuals with post-stroke speech impairment via telehealth in a Phase 0 clinical trial. Results suggest that impaired speech can be elicited by startling acoustic stimuli and that START benefits individuals with severe-to-moderate post-stroke impairments in both linguistic and motor speech domains. This fills an important gap in aphasia care, as many speech therapies remain ineffective and financially inaccessible for patients with severe deficits. START is effective, remotely delivered, and may likely serve as an affordable adjuvant to traditional therapy for those that have poor access to quality care.
ContributorsSwann, Zoe Elisabeth (Author) / Honeycutt, Claire F (Thesis advisor) / Daliri, Ayoub (Committee member) / Rogalsky, Corianne (Committee member) / Liss, Julie (Committee member) / Schaefer, Sydney (Committee member) / Arizona State University (Publisher)
Created2022
Description
There are many inconsistencies in the literature regarding how to estimate the Lyapunov Exponent (LyE) for gait. In the last decade, many papers have been published using Lyapunov Exponents to determine differences between young healthy and elderly adults and healthy and frail older adults. However, the differences in methodologies of data collection, input parameters, and algorithms used for the LyE calculation has led to conflicting numerical values for the literature to build upon. Without a unified methodology for calculating the LyE, researchers can only look at the trends found in studies. For instance, LyE is generally lower for young adults compared to elderly adults, but these values cannot be correlated across studies to create a classifier for individuals that are healthy or at-risk of falling. These issues could potentially be solved by standardizing the process of computing the LyE.
This dissertation examined several hurdles that must be overcome to create a standardized method of calculating the LyE for gait data when collected with an accelerometer. In each of the following investigations, both the Rosenstein et al. and Wolf et al. algorithms as well as three normalization methods were applied in order to understand the extent at which these factors affect the LyE. First, the a priori parameters of time delay and embedding dimension which are required for phase space reconstruction were investigated. This study found that the time delay can be standardized to a value of 10 and that an embedding dimension of 5 or 7 should be used for the Rosenstein and Wolf algorithm respectively. Next, the effect of data length on the LyE was examined using 30 to 1300 strides of gait data. This analysis found that comparisons across papers are only possible when similar amounts of data are used but comparing across normalization methods is not recommended. And finally, the reliability and minimum required number of strides for each of the 6 algorithm-normalization method combinations in both young healthy and elderly adults was evaluated. This research found that the Rosenstein algorithm was more reliable and required fewer strides for the calculation of the LyE for an accelerometer.
This dissertation examined several hurdles that must be overcome to create a standardized method of calculating the LyE for gait data when collected with an accelerometer. In each of the following investigations, both the Rosenstein et al. and Wolf et al. algorithms as well as three normalization methods were applied in order to understand the extent at which these factors affect the LyE. First, the a priori parameters of time delay and embedding dimension which are required for phase space reconstruction were investigated. This study found that the time delay can be standardized to a value of 10 and that an embedding dimension of 5 or 7 should be used for the Rosenstein and Wolf algorithm respectively. Next, the effect of data length on the LyE was examined using 30 to 1300 strides of gait data. This analysis found that comparisons across papers are only possible when similar amounts of data are used but comparing across normalization methods is not recommended. And finally, the reliability and minimum required number of strides for each of the 6 algorithm-normalization method combinations in both young healthy and elderly adults was evaluated. This research found that the Rosenstein algorithm was more reliable and required fewer strides for the calculation of the LyE for an accelerometer.
ContributorsSmith, Victoria (Author) / Lockhart, Thurmon E (Thesis advisor) / Spano, Mark L (Committee member) / Honeycutt, Claire F (Committee member) / Lee, Hyunglae (Committee member) / Peterson, Daniel S (Committee member) / Arizona State University (Publisher)
Created2019