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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

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
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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

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
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Description
Previous research has shown that a loud acoustic stimulus can trigger an individual's prepared movement plan. This movement response is referred to as a startle-evoked movement (SEM). SEM has been observed in the stroke survivor population where results have shown that SEM enhances single joint movements that are usually performed

Previous research has shown that a loud acoustic stimulus can trigger an individual's prepared movement plan. This movement response is referred to as a startle-evoked movement (SEM). SEM has been observed in the stroke survivor population where results have shown that SEM enhances single joint movements that are usually performed with difficulty. While the presence of SEM in the stroke survivor population advances scientific understanding of movement capabilities following a stroke, published studies using the SEM phenomenon only examined one joint. The ability of SEM to generate multi-jointed movements is understudied and consequently limits SEM as a potential therapy tool. In order to apply SEM as a therapy tool however, the biomechanics of the arm in multi-jointed movement planning and execution must be better understood. Thus, the objective of our study was to evaluate if SEM could elicit multi-joint reaching movements that were accurate in an unrestrained, two-dimensional workspace. Data was collected from ten subjects with no previous neck, arm, or brain injury. Each subject performed a reaching task to five Targets that were equally spaced in a semi-circle to create a two-dimensional workspace. The subject reached to each Target following a sequence of two non-startling acoustic stimuli cues: "Get Ready" and "Go". A loud acoustic stimuli was randomly substituted for the "Go" cue. We hypothesized that SEM is accessible and accurate for unrestricted multi-jointed reaching tasks in a functional workspace and is therefore independent of movement direction. Our results found that SEM is possible in all five Target directions. The probability of evoking SEM and the movement kinematics (i.e. total movement time, linear deviation, average velocity) to each Target are not statistically different. Thus, we conclude that SEM is possible in a functional workspace and is not dependent on where arm stability is maximized. Moreover, coordinated preparation and storage of a multi-jointed movement is indeed possible.
ContributorsOssanna, Meilin Ryan (Author) / Honeycutt, Claire (Thesis director) / Schaefer, Sydney (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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Description
This dissertation research investigates the social implications of computing artifacts that make use of sensor driven self-quantification to implicitly or explicitly direct user behaviors. These technologies are referred to here as self-sensoring prescriptive applications (SSPA’s). This genre of technological application has a strong presence in healthcare as a means to

This dissertation research investigates the social implications of computing artifacts that make use of sensor driven self-quantification to implicitly or explicitly direct user behaviors. These technologies are referred to here as self-sensoring prescriptive applications (SSPA’s). This genre of technological application has a strong presence in healthcare as a means to monitor health, modify behavior, improve health outcomes, and reduce medical costs. However, the commercial sector is quickly adopting SSPA’s as a means to monitor and/or modify consumer behaviors as well (Swan, 2013). These wearable devices typically monitor factors such as movement, heartrate, and respiration; ostensibly to guide the users to better or more informed choices about their physical fitness (Lee & Drake, 2013; Swan, 2012b). However, applications that claim to use biosensor data to assist in mood maintenance and control are entering the market (Bolluyt, 2015), and applications to aid in decision making about consumer products are on the horizon as well (Swan, 2012b). Interestingly, there is little existing research that investigates the direct impact biosensor data have on decision making, nor on the risks, benefits, or regulation of such technologies. The research presented here is inspired by a number of separate but related gaps in existing literature about the social implications of SSPA’s. First, how SSPA’s impact individual and group decision making and attitude formation within non-medical-care domains (e.g. will a message about what product to buy be more persuasive if it claims to have based the recommendation on your biometric information?). Second, how the design and designers of SSPA’s shape social behaviors and third, how these factors are or are not being considered in future design and public policy decisions.
ContributorsBaker, Denise A (Author) / Schweitzer, Nicholas J (Thesis advisor) / Wise, J. MacGregor (Thesis advisor) / Herkert, Joseph R (Committee member) / McDaniel, Troy (Committee member) / Arizona State University (Publisher)
Created2016
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Description
There are 6 methods of persuasion: reciprocity, scarcity, authority, commitment, liking, and social proof. Although these are typically used in economic scenarios, they may be present between professors and their students as well. We surveyed ASU students to find out which methods of persuasion professors may be implementing in their

There are 6 methods of persuasion: reciprocity, scarcity, authority, commitment, liking, and social proof. Although these are typically used in economic scenarios, they may be present between professors and their students as well. We surveyed ASU students to find out which methods of persuasion professors may be implementing in their classrooms, and whether or not these were effective in improving student outcomes (performance, memory, etc.).
ContributorsPautz, Daniella (Author) / Honeycutt, Claire (Thesis director) / Krause, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2022-05