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Description
This research is focused on two separate but related topics. The first uses an electroencephalographic (EEG) brain-computer interface (BCI) to explore the phenomenon of motor learning transfer. The second takes a closer look at the EEG-BCI itself and tests an alternate way of mapping EEG signals into machine commands. We

This research is focused on two separate but related topics. The first uses an electroencephalographic (EEG) brain-computer interface (BCI) to explore the phenomenon of motor learning transfer. The second takes a closer look at the EEG-BCI itself and tests an alternate way of mapping EEG signals into machine commands. We test whether motor learning transfer is more related to use of shared neural structures between imagery and motor execution or to more generalized cognitive factors. Using an EEG-BCI, we train one group of participants to control the movements of a cursor using embodied motor imagery. A second group is trained to control the cursor using abstract motor imagery. A third control group practices moving the cursor using an arm and finger on a touch screen. We hypothesized that if motor learning transfer is related to the use of shared neural structures then the embodied motor imagery group would show more learning transfer than the abstract imaging group. If, on the other hand, motor learning transfer results from more general cognitive processes, then the abstract motor imagery group should also demonstrate motor learning transfer to the manual performance of the same task. Our findings support that motor learning transfer is due to the use of shared neural structures between imaging and motor execution of a task. The abstract group showed no motor learning transfer despite being better at EEG-BCI control than the embodied group. The fact that more participants were able to learn EEG-BCI control using abstract imagery suggests that abstract imagery may be more suitable for EEG-BCIs for some disabilities, while embodied imagery may be more suitable for others. In Part 2, EEG data collected in the above experiment was used to train an artificial neural network (ANN) to map EEG signals to machine commands. We found that our open-source ANN using spectrograms generated from SFFTs is fundamentally different and in some ways superior to Emotiv's proprietary method. Our use of novel combinations of existing technologies along with abstract and embodied imagery facilitates adaptive customization of EEG-BCI control to meet needs of individual users.
Contributorsda Silva, Flavio J. K (Author) / Mcbeath, Michael K (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Presson, Clark (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This research study investigated the effects of high fidelity graphics on both learning and presence, or the "sense of being there," inside a Virtual Learning Environment (VLE). Four versions of a VLE on the subject of the element mercury were created, each with a different combination of high and

This research study investigated the effects of high fidelity graphics on both learning and presence, or the "sense of being there," inside a Virtual Learning Environment (VLE). Four versions of a VLE on the subject of the element mercury were created, each with a different combination of high and low fidelity polygon models and high and low fidelity shaders. A total of 76 college age (18+ years of age) participants were randomly assigned to one of the four conditions. The participants interacted with the VLE and then completed several posttest measures on learning, presence, and attitudes towards the VLE experience. Demographic information was also collected, including age, computer gameplay experience, number of virtual environments interacted with, gender and time spent in this virtual environment. The data was analyzed as a 2 x 2 between subjects ANOVA.

The main effects of shader fidelity and polygon fidelity were both non- significant for both learning and all presence subscales inside the VLE. In addition, there was no significant interaction between shader fidelity and model fidelity. However, there were two significant results on the supplementary variables. First, gender was found to have a significant main effect on all the presence subscales. Females reported higher average levels of presence than their male counterparts. Second, gameplay hours, or the number of hours a participant played computer games per week, also had a significant main effect on participant score on the learning measure. The participants who reported playing 15+ hours of computer games per week, the highest amount of time in the variable, had the highest score as a group on the mercury learning measure while those participants that played 1-5 hours per week had the lowest scores.
ContributorsHorton, Scott (Author) / Nelson, Brian (Thesis advisor) / Savenye, Wilhelmina (Committee member) / Atkinson, Robert (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Many web search improvements have been developed since the advent of the modern search engine, but one underrepresented area is the application of specific customizations to search results for educational web sites. In order to address this issue and improve the relevance of search results in automated learning environments, this

Many web search improvements have been developed since the advent of the modern search engine, but one underrepresented area is the application of specific customizations to search results for educational web sites. In order to address this issue and improve the relevance of search results in automated learning environments, this work has integrated context-aware search principles with applications of preference based re-ranking and query modifications. This research investigates several aspects of context-aware search principles, specifically context-sensitive and preference based re-ranking of results which take user inputs as to their preferred content, and combines this with search query modifications which automatically search for a variety of modified terms based on the given search query, integrating these results into the overall re-ranking for the context. The result of this work is a novel web search algorithm which could be applied to any online learning environment attempting to collect relevant resources for learning about a given topic. The algorithm has been evaluated through user studies comparing traditional search results to the context-aware results returned through the algorithm for a given topic. These studies explore how this integration of methods could provide improved relevance in the search results returned when compared against other modern search engines.
ContributorsVan Egmond, Eric (Author) / Burleson, Winslow (Thesis advisor) / Syrotiuk, Violet (Thesis advisor) / Nelson, Brian (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Epilepsy is a group of disorders that cause seizures in approximately 2.2 million people in the United States. Over 30% of these patients have epilepsies that do not respond to treatment with anti-epileptic drugs. For this population, focal resection surgery could offer long-term seizure freedom. Surgery candidates undergo a myriad

Epilepsy is a group of disorders that cause seizures in approximately 2.2 million people in the United States. Over 30% of these patients have epilepsies that do not respond to treatment with anti-epileptic drugs. For this population, focal resection surgery could offer long-term seizure freedom. Surgery candidates undergo a myriad of tests and monitoring to determine where and when seizures occur. The “gold standard” method for focus identification involves the placement of electrocorticography (ECoG) grids in the sub-dural space, followed by continual monitoring and visual inspection of the patient’s cortical activity. This process, however, is highly subjective and uses dated technology. Multiple studies were performed to investigate how the evaluation process could benefit from an algorithmic adjust using current ECoG technology, and how the use of new microECoG technology could further improve the process.

Computational algorithms can quickly and objectively find signal characteristics that may not be detectable with visual inspection, but many assume the data are stationary and/or linear, which biological data are not. An empirical mode decomposition (EMD) based algorithm was developed to detect potential seizures and tested on data collected from eight patients undergoing monitoring for focal resection surgery. EMD does not require linearity or stationarity and is data driven. The results suggest that a biological data driven algorithm could serve as a useful tool to objectively identify changes in cortical activity associated with seizures.

Next, the use of microECoG technology was investigated. Though both ECoG and microECoG grids are composed of electrodes resting on the surface of the cortex, changing the diameter of the electrodes creates non-trivial changes in the physics of the electrode-tissue interface that need to be accounted for. Experimenting with different recording configurations showed that proper grounding, referencing, and amplification are critical to obtain high quality neural signals from microECoG grids.

Finally, the relationship between data collected from the cortical surface with micro and macro electrodes was studied. Simultaneous recordings of the two electrode types showed differences in power spectra that suggest the inclusion of activity, possibly from deep structures, by macroelectrodes that is not accessible by microelectrodes.
ContributorsAshmont, Kari Rich (Author) / Greger, Bradley (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Buneo, Christopher (Committee member) / Adelson, P David (Committee member) / Dudek, F Edward (Committee member) / Arizona State University (Publisher)
Created2015
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Description
A previous study demonstrated that learning to lift an object is context-based and that in the presence of both the memory and visual cues, the acquired sensorimotor memory to manipulate an object in one context interferes with the performance of the same task in presence of visual information about a

A previous study demonstrated that learning to lift an object is context-based and that in the presence of both the memory and visual cues, the acquired sensorimotor memory to manipulate an object in one context interferes with the performance of the same task in presence of visual information about a different context (Fu et al, 2012).
The purpose of this study is to know whether the primary motor cortex (M1) plays a role in the sensorimotor memory. It was hypothesized that temporary disruption of the M1 following the learning to minimize a tilt using a ‘L’ shaped object would negatively affect the retention of sensorimotor memory and thus reduce interference between the memory acquired in one context and the visual cues to perform the same task in a different context.
Significant findings were shown in blocks 1, 2, and 4. In block 3, subjects displayed insignificant amount of learning. However, it cannot be concluded that there is full interference in block 3. Therefore, looked into 3 effects in statistical analysis: the main effects of the blocks, the main effects of the trials, and the effects of the blocks and trials combined. From the block effects, there is a p-value of 0.001, and from the trial effects, the p-value is less than 0.001. Both of these effects indicate that there is learning occurring. However, when looking at the blocks * trials effects, we see a p-value of 0.002 < 0.05 indicating significant interaction between sensorimotor memories. Based on the results that were found, there is a presence of interference in all the blocks but not enough to justify the use of TMS in order to reduce interference because there is a partial reduction of interference from the control experiment. It is evident that the time delay might be the issue between context switches. By reducing the time delay between block 2 and 3 from 10 minutes to 5 minutes, I will hope to see significant learning to occur from the first trial to the second trial.
ContributorsHasan, Salman Bashir (Author) / Santello, Marco (Thesis director) / Kleim, Jeffrey (Committee member) / Helms Tillery, Stephen (Committee member) / Barrett, The Honors College (Contributor) / W. P. Carey School of Business (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
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Description
Electroencephalogram (EEG) used simultaneously with video monitoring can record detailed patient physiology during a seizure to aid diagnosis. However, current patient monitoring systems typically require a patient to stay in view of a fixed camera limiting their freedom of movement. The goal of this project is to design an automatic

Electroencephalogram (EEG) used simultaneously with video monitoring can record detailed patient physiology during a seizure to aid diagnosis. However, current patient monitoring systems typically require a patient to stay in view of a fixed camera limiting their freedom of movement. The goal of this project is to design an automatic patient monitoring system with software to track patient movement in order to increase a patient's mobility. This report discusses the impact of an automatic patient monitoring system and the design steps used to create and test a functional prototype.
ContributorsBui, Robert Truong (Author) / Frakes, David (Thesis director) / Helms Tillery, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2014-05
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Description
Brain-computer interface technology establishes communication between the brain and a computer, allowing users to control devices, machines, or virtual objects using their thoughts. This study investigates optimal conditions to facilitate learning to operate this interface. It compares two biofeedback methods, which dictate the relationship between brain activity and the movement

Brain-computer interface technology establishes communication between the brain and a computer, allowing users to control devices, machines, or virtual objects using their thoughts. This study investigates optimal conditions to facilitate learning to operate this interface. It compares two biofeedback methods, which dictate the relationship between brain activity and the movement of a virtual ball in a target-hitting task. Preliminary results indicate that a method in which the position of the virtual object directly relates to the amplitude of brain signals is most conducive to success. In addition, this research explores learning in the context of neural signals during training with a BCI task. Specifically, it investigates whether subjects can adapt to parameters of the interface without guidance. This experiment prompts subjects to modulate brain signals spectrally, spatially, and temporally, as well differentially to discriminate between two different targets. However, subjects are not given knowledge regarding these desired changes, nor are they given instruction on how to move the virtual ball. Preliminary analysis of signal trends suggests that some successful participants are able to adapt brain wave activity in certain pre-specified locations and frequency bands over time in order to achieve control. Future studies will further explore these phenomena, and future BCI projects will be advised by these methods, which will give insight into the creation of more intuitive and reliable BCI technology.
ContributorsLancaster, Jenessa Mae (Co-author) / Appavu, Brian (Co-author) / Wahnoun, Remy (Co-author, Committee member) / Helms Tillery, Stephen (Thesis director) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / Department of Psychology (Contributor)
Created2014-05
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Description
Motor behavior is prone to variable conditions and deviates further in disorders affecting the nervous system. A combination of environmental and neural factors impacts the amount of uncertainty. Although the influence of these factors on estimating endpoint positions have been examined, the role of limb configuration on endpoint variability has

Motor behavior is prone to variable conditions and deviates further in disorders affecting the nervous system. A combination of environmental and neural factors impacts the amount of uncertainty. Although the influence of these factors on estimating endpoint positions have been examined, the role of limb configuration on endpoint variability has been mostly ignored. Characterizing the influence of arm configuration (i.e. intrinsic factors) would allow greater comprehension of sensorimotor integration and assist in interpreting exaggerated movement variability in patients. In this study, subjects were placed in a 3-D virtual reality environment and were asked to move from a starting position to one of three targets in the frontal plane with and without visual feedback of the moving limb. The alternating of visual feedback during trials increased uncertainty between the planning and execution phases. The starting limb configurations, adducted and abducted, were varied in separate blocks. Arm configurations were setup by rotating along the shoulder-hand axis to maintain endpoint position. The investigation hypothesized: 1) patterns of endpoint variability of movements would be dependent upon the starting arm configuration and 2) any differences observed would be more apparent in conditions that withheld visual feedback. The results indicated that there were differences in endpoint variability between arm configurations in both visual conditions, but differences in variability increased when visual feedback was withheld. Overall this suggests that in the presence of visual feedback, planning of movements in 3D space mostly uses coordinates that are arm configuration independent. On the other hand, without visual feedback, planning of movements in 3D space relies substantially on intrinsic coordinates.
ContributorsRahman, Qasim (Author) / Buneo, Christopher (Thesis director) / Helms Tillery, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
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Description
Motor behavior is prone to variable conditions and deviates further in disorders affecting the nervous system. A combination of environmental and neural factors impacts the amount of uncertainty. Although the influence of these factors on estimating endpoint positions have been examined, the role of limb configuration on endpoint variability has

Motor behavior is prone to variable conditions and deviates further in disorders affecting the nervous system. A combination of environmental and neural factors impacts the amount of uncertainty. Although the influence of these factors on estimating endpoint positions have been examined, the role of limb configuration on endpoint variability has been mostly ignored. Characterizing the influence of arm configuration (i.e. intrinsic factors) would allow greater comprehension of sensorimotor integration and assist in interpreting exaggerated movement variability in patients. In this study, subjects were placed in a 3-D virtual reality environment and were asked to move from a starting position to one of three targets in the frontal plane with and without visual feedback of the moving limb. The alternating of visual feedback during trials increased uncertainty between the planning and execution phases. The starting limb configurations, adducted and abducted, were varied in separate blocks. Arm configurations were setup by rotating along the shoulder-hand axis to maintain endpoint position. The investigation hypothesized: 1) patterns of endpoint variability of movements would be dependent upon the starting arm configuration and 2) any differences observed would be more apparent in conditions that withheld visual feedback. The results indicated that there were differences in endpoint variability between arm configurations in both visual conditions, but differences in variability increased when visual feedback was withheld. Overall this suggests that in the presence of visual feedback, planning of movements in 3D space mostly uses coordinates that are arm configuration independent. On the other hand, without visual feedback, planning of movements in 3D space relies substantially on intrinsic coordinates.
ContributorsRahman, Qasim (Author) / Buneo, Christopher (Thesis director) / Helms Tillery, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
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Description
Can a skill taught in a virtual environment be utilized in the physical world? This idea is explored by creating a Virtual Reality game for the HTC Vive to teach users how to play the drums. The game focuses on developing the user's muscle memory, improving the user's ability to

Can a skill taught in a virtual environment be utilized in the physical world? This idea is explored by creating a Virtual Reality game for the HTC Vive to teach users how to play the drums. The game focuses on developing the user's muscle memory, improving the user's ability to play music as they hear it in their head, and refining the user's sense of rhythm. Several different features were included to achieve this such as a score, different levels, a demo feature, and a metronome. The game was tested for its ability to teach and for its overall enjoyability by using a small sample group. Most participants of the sample group noted that they felt as if their sense of rhythm and drumming skill level would improve by playing the game. Through the findings of this project, it can be concluded that while it should not be considered as a complete replacement for traditional instruction, a virtual environment can be successfully used as a learning aid and practicing tool.
ContributorsDinapoli, Allison (Co-author) / Tuznik, Richard (Co-author) / Kobayashi, Yoshihiro (Thesis director) / Nelson, Brian (Committee member) / Computer Science and Engineering Program (Contributor) / School of International Letters and Cultures (Contributor) / Computing and Informatics Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12