Barrett, The Honors College Thesis/Creative Project Collection
Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.
Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.
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- Creators: Harrington Bioengineering Program
Description
Most daily living tasks consist of pairing a series of sequential movements, e.g., reaching to a cup, grabbing the cup, lifting and returning the cup to your mouth. The process by which we control and mediate the smooth progression of these tasks is not well understood. One method which we can use to further evaluate these motions is known as Startle Evoked Movements (SEM). SEM is an established technique to probe the motor learning and planning processes by detecting muscle activation of the sternocleidomastoid muscles of the neck prior to 120ms after a startling stimulus is presented. If activation of these muscles was detected following a stimulus in the 120ms window, the movement is classified as Startle+ whereas if no sternocleidomastoid activation is detected after a stimulus in the allotted time the movement is considered Startle-. For a movement to be considered SEM, the activation of movements for Startle+ trials must be faster than the activation of Startle- trials. The objective of this study was to evaluate the effect that expertise has on sequential movements as well as determining if startle can distinguish when the consolidation of actions, known as chunking, has occurred. We hypothesized that SEM could distinguish words that were solidified or chunked. Specifically, SEM would be present when expert typists were asked to type a common word but not during uncommon letter combinations. The results from this study indicated that the only word that was susceptible to SEM, where Startle+ trials were initiated faster than Startle-, was an uncommon task "HET" while the common words "AND" and "THE" were not. Additionally, the evaluation of the differences between each keystroke for common and uncommon words showed that Startle was unable to distinguish differences in motor chunking between Startle+ and Startle- trials. Explanations into why these results were observed could be related to hand dominance in expert typists. No proper research has been conducted to evaluate the susceptibility of the non-dominant hand's fingers to SEM, and the results of future studies into this as well as the results from this study can impact our understanding of sequential movements.
ContributorsMieth, Justin Richard (Author) / Honeycutt, Claire (Thesis director) / Santello, Marco (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This project aims to use the shape memory alloy nitinol as the basis for a biomimetic actuator. These actuators are designed to mimic the behavior of organic muscles for use in prosthetic and robotic devices. Actuator characterization included in the project examines the force output,electrical properties, and other variables relevant to actuator design.
ContributorsNoe, Cameron Scott (Author) / LaBelle, Jeffrey (Thesis director) / Santello, Marco (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
Startle-evoked-movement (SEM), the involuntary release of a planned movement via a startling stimulus, has gained significant attention recently for its ability to probe motor planning as well as enhance movement of the upper extremity following stroke. We recently showed that hand movements are susceptible to SEM. Interestingly, only coordinated movements of the hand (grasp) but not individuated movements of the finger (finger abduction) were susceptible. It was suggested that this resulted from different neural mechanisms involved in each task; however it is possible this was the result of task familiarity. The objective of this study was to evaluate a more familiar individuated finger movement, typing, to determine if this task was susceptible to SEM. We hypothesized that typing movements will be susceptible to SEM in all fingers. These results indicate that individuated movements of the fingers are susceptible to SEM when the task involves a more familiar task, since the electromyogram (EMG) latency is faster in SCM+ trials compared to SCM- trials. However, the middle finger does not show a difference in terms of the keystroke voltage signal, suggesting the middle finger is less susceptible to SEM. Given that SEM is thought to be mediated by the brainstem, specifically the reticulospinal tract, this suggest that the brainstem may play a role in movements of the distal limb when those movements are very familiar, and the independence of each finger might also have a significant on the effect of SEM. Further research includes understanding SEM in fingers in the stroke population. The implications of this research can impact the way upper extremity rehabilitation is delivered.
ContributorsQuezada Valladares, Maria Jose (Author) / Honeycutt, Claire (Thesis director) / Santello, Marco (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
In 1937 Canadian neurosurgeon Wilder Penfield made the first to attempt to map the sensorimotor cortex of the human brain in his paper entitled Somatic Motor and Sensory Representation in the Cerebral Cortex of Man as Studied by Electrical Stimulation. While analogous experimentation had been carried out previously using animal subjects, Penfield sought to understand the delicate and complex neuronal pathways that served as the hidden control mechanisms for human activity. The motor homunculus that followed from his findings has been widely accepted as the standard model for the relative spatial representation of the functionality of the motor cortex, and has been virtually unaltered since its inception. While Penfield took measures to collect cortical data in a manner as accurately as scientifically possible for the time period, his original model is deserving of further analysis using modern techniques. This study uses functional magnetic resonance imaging (fMRI) to quantitatively determine motor function volumes and spatial relationships for four motor tasks: toe, finger, eyebrow, and tongue. Although Penfield's general representation of the superior-to-inferior spatial distribution of the motor cortex was replicated with reasonable accuracy, relative mean task volumes seem to differ from Penfield's original model. The data was first analyzed in each individual patient's native anatomical space for task comparison within a single subject. The volumes of the motor cortex devoted to the eyebrow and toe tasks, which comprise only small portions of the Penfield homunculus, are shown to be relatively large in their fMRI representation compared to finger and tongue. However, these tasks have large deviation values, indicating a lack of consistency in task volume size among patients. Behaviorally, toe movement may include whole foot movement in some individuals, and eyebrows may include face movement, causing distributions that are more widespread. The data was then analyzed in the Montreal Neurological Institute (MNI) space, which is mathematically normalized for task comparison between different subjects. Tongue and finger tasks were the largest in volume, much like Penfield's model. However, they also had substantial deviation, again indicating task volume size inconsistencies. Since the Penfield model is only a qualitative spatial evaluation of motor function along the precentral gyrus, numerical deviation from the model cannot necessarily be quantified. Hence, the results of this study can be interpreted standalone without a current comparison. While future research will serve to further validate these distances and volumes, this quantitative model of the functionality of the motor cortex will be of great utility for future neurological research and during preoperative evaluations of neurosurgical patients.
ContributorsOland, Gabriel Lee (Author) / Frakes, David (Thesis director) / Santello, Marco (Committee member) / Baxter, Leslie (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05
Description
Electrochemical sensors function by detecting electroactive species at the electrode surface of a screen printed sensor. As more force is applied, the concentration of electroactive species at the surface of the sensor increases and a larger current is measured. Thus, when all conditions including voltage are made constant, as in Amp i-t, a quantifiable current can be read and the force applied can be calculated. Two common electrochemical techniques in which current is measured, cyclic voltammetry(CV) and amperometric i-t(Amp i-t), were used. A compressible sensor capable of transducing a force and acquiring feedback was created.
ContributorsFeldman, Austin Marc (Author) / LaBelle, Jeffrey (Thesis director) / Pizziconi, Vincent (Committee member) / Santello, Marco (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05
Description
The importance of nonverbal communication has been well established through several theories including Albert Mehrabian's 7-38-55 rule that proposes the respective importance of semantics, tonality and facial expressions in communication. Although several studies have examined how emotions are expressed and preceived in communication, there is limited research investigating the relationship between how emotions are expressed through semantics and facial expressions. Using a facial expression analysis software to deconstruct facial expressions into features and a K-Nearest-Neighbor (KNN) machine learning classifier, we explored if facial expressions can be clustered based on semantics. Our findings indicate that facial expressions can be clustered based on semantics and that there is an inherent congruence between facial expressions and semantics. These results are novel and significant in the context of nonverbal communication and are applicable to several areas of research including the vast field of emotion AI and machine emotional communication.
ContributorsEverett, Lauren (Author) / Coza, Aurel (Thesis director) / Santello, Marco (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / Dean, W.P. Carey School of Business (Contributor)
Created2022-05