This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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Description
Spasticity is a neurological disorder in which a target group of muscles remain in a contracted state. In addition to interfering with the function of these muscles, spasticity causes chronic pain and discomfort. Often found in patients with cerebral palsy, multiple sclerosis, or stroke history, spasticity affects an estimated twelve

Spasticity is a neurological disorder in which a target group of muscles remain in a contracted state. In addition to interfering with the function of these muscles, spasticity causes chronic pain and discomfort. Often found in patients with cerebral palsy, multiple sclerosis, or stroke history, spasticity affects an estimated twelve million people worldwide. Not only does spasticity cause discomfort and loss of function, but the condition can lead to contractures, or permanent shortenings of the muscle and connective tissue, if left untreated. Current treatments for spasticity are primarily different forms of muscle relaxant pharmaceuticals. Almost all of these drugs, however, carry unwanted side effects, including total muscle weakness, liver toxicity, and possible dependence. Additionally, kinesiotherapy, conducted by physical therapists at rehabilitation clinics, is often prescribed to people suffering from spasticity. Since kinesiotherapy requires frequent practice to be effective, proper treatment requires constant professional care and clinic appointments, discouraging patient compliance. Consequently, a medical device that could automate relief for spasticity outside of a clinic is desired in the market. While a number of different dynamic splints for hand spasticity are currently on the market, research has shown that these devices, which simply brace the hand in an extended position, do not work through any mechanism to decrease spastic tension over time. Two methods of temporarily reducing spasticity that have been observed in clinical studies are cryotherapy, or the decrease of temperature on a target area, and electrotherapy, which is the delivery of regulated electrical pulses to a target area. It is possible that either of these mechanisms could be incorporated into a medical device aimed toward spastic relief. In fact, electrotherapy is used in a current market device called the SaeboStim, which is advertised to help stroke recovery and spastic reduction. The purpose of this paper is to evaluate the viability of a potential spastic relief device that utilizes cryotherapy to a current and closest competitor, the SaeboStim. The effectiveness of each device in relieving spasticity is reviewed. The two devices are also compared on their ability to address primary customer needs, such as convenience, ease of use, durability, and price. Overall, it is concluded that the cryotherapy device more effectively relieves hand spasticity in users, although the SaeboStim's smaller size and better convenience gives it market appeal, and reveals some of the shortcomings in the preliminary design of the cryotherapy device.
ContributorsWiedeman, Christopher Blaise (Author) / Kleim, Jeffrey (Thesis director) / Buneo, Christopher (Committee member) / W.P. Carey School of Business (Contributor) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Brain-machine interfaces (BMIs) were first imagined as a technology that would allow subjects to have direct communication with prosthetics and external devices (e.g. control over a computer cursor or robotic arm movement). Operation of these devices was not automatic, and subjects needed calibration and training in order to master this

Brain-machine interfaces (BMIs) were first imagined as a technology that would allow subjects to have direct communication with prosthetics and external devices (e.g. control over a computer cursor or robotic arm movement). Operation of these devices was not automatic, and subjects needed calibration and training in order to master this control. In short, learning became a key component in controlling these systems. As a result, BMIs have become ideal tools to probe and explore brain activity, since they allow the isolation of neural inputs and systematic altering of the relationships between the neural signals and output. I have used BMIs to explore the process of brain adaptability in a motor-like task. To this end, I trained non-human primates to control a 3D cursor and adapt to two different perturbations: a visuomotor rotation, uniform across the neural ensemble, and a decorrelation task, which non-uniformly altered the relationship between the activity of particular neurons in an ensemble and movement output. I measured individual and population level changes in the neural ensemble as subjects honed their skills over the span of several days. I found some similarities in the adaptation process elicited by these two tasks. On one hand, individual neurons displayed tuning changes across the entire ensemble after task adaptation: most neurons displayed transient changes in their preferred directions, and most neuron pairs showed changes in their cross-correlations during the learning process. On the other hand, I also measured population level adaptation in the neural ensemble: the underlying neural manifolds that control these neural signals also had dynamic changes during adaptation. I have found that the neural circuits seem to apply an exploratory strategy when adapting to new tasks. Our results suggest that information and trajectories in the neural space increase after initially introducing the perturbations, and before the subject settles into workable solutions. These results provide new insights into both the underlying population level processes in motor learning, and the changes in neural coding which are necessary for subjects to learn to control neuroprosthetics. Understanding of these mechanisms can help us create better control algorithms, and design training paradigms that will take advantage of these processes.
ContributorsArmenta Salas, Michelle (Author) / Helms Tillery, Stephen I (Thesis advisor) / Si, Jennie (Committee member) / Buneo, Christopher (Committee member) / Santello, Marco (Committee member) / Kleim, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2015