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I worked on the human-machine interface to improve human physical capability. This work was done in the Human Oriented Robotics and Control Lab (HORC) towards the creation of an advanced, EMG-controlled exoskeleton. The project was new, and any work on the human- machine interface needs the physical interface itself. So I designed and fabricated a human-robot coupling device with a novel safety feature. The validation testing of this coupling proved very successful, and the device was granted a provisional patent as well as published to facilitate its spread to other human-machine interface applications, where it could be of major benefit. I then employed this coupling in experimentation towards understanding impedance, with the end goal being the creation of an EMG-based impedance exoskeleton control system. I modified a previously established robot-to-human perturbation method for use in my novel, three- dimensional (3D) impedance measurement experiment. Upon execution of this experiment, I was able to successfully characterize passive, static human arm stiffness in 3D, and in doing so validated the aforementioned method. This establishes an important foundation for promising future work on understanding impedance and the creation of the proposed control scheme, thereby furthering the field of human-robot interaction.
ContributorsO'Neill, Gerald D. (Author) / Artemiadis, Panagiotis (Thesis director) / Santello, Marco (Committee member) / Santos, Veronica (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2013-05
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
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.
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
Description
Electromyography (EMG) and Electroencephalography (EEG) are techniques used to detect electrical activity produced by the human body. EMG detects electrical activity in the skeletal muscles, while EEG detects electrical activity from the scalp. The purpose of this study is to capture different types of EMG and EEG signals and to determine if the signals can be distinguished between each other and processed into output signals to trigger events in prosthetics. Results from the study suggest that the PSD estimates can be used to compare signals that have significant differences such as the wrist, scalp, and fingers, but it cannot fully distinguish between signals that are closely related, such as two different fingers. The signals that were identified were able to be translated into the physical output simulated on the Arduino circuit.
ContributorsJanis, William Edward (Author) / LaBelle, Jeffrey (Thesis director) / Santello, Marco (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-12
Description
Methicillin-Resistant Staphylococcus aureus (MRSA) infections are a major challenge to healthcare professionals. Treatment of MRSA is expensive, and otherwise avoidable deaths occur every year in the United States due to MRSA infections. Additionally, such infections lengthen patients’ stays in hospitals, keeping them out of work and adversely affecting the economy. Beta lactam antibiotics used to be highly effective against S. aureus infections, but resistance mechanisms have rendered methicillin, oxacillin, and other beta lactam antibiotics ineffective against these infections. A promising avenue for MRSA treatment lies in the use of synthetic antibodies—molecules that bind with specificity to a given compound. Synbody 14 is an example of such a synbody, and has been designed with MRSA treatment in mind. Mouse model studies have even associated Syn14 treatment with reduced weight loss and morbidity in MRSA-infected mice. In this experiment, in vitro activity of Syn 14 and oxacillin was assessed. Early experiments measured Syn 14 and oxacillin’s effectiveness in inhibiting colony growth in growth media, mouse serum, and mouse blood. Syn14 and oxacillin had limited efficacy against USA300 strain MRSA, though interestingly it was noted that Syn14 outperformed oxacillin in mouse serum and whole mouse blood, indicating the benefits of its binding properties. A second experiment measured the impact that a mix of oxacillin and Syn 14 had on colony growth, as well as the effect of adding them simultaneously or one after the other. While use of either bactericidal alone did not show a major inhibitory effect on USA300 MRSA colony growth, their use in combination showed major decreases in colony growth. Moreover, it was found that unlike other combination therapies, Syn14 and oxacillin did not require simultaneous addition to MRSA cells to achieve inhibition of cell growth. They merely required that Syn14 be added first. This result suggests Syn14’s possible utility in therapeutic settings, as the time insensitivity of synergy removes a major hurdle to clinical use—the difficulty in ensuring that two drugs reach an affected area at the same time. Syn14 remains a promising antimicrobial agent, and further study should focus on its precise mechanism of action and suitability in clinical treatment of MRSA infections.
ContributorsMichael, Alexander (Author) / Diehnelt, Chris (Thesis director) / Stafford, Phillip (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
Description
Peptides offer great promise as targeted affinity ligands, but the space of possible peptide sequences is vast, making experimental identification of lead candidates expensive, difficult, and uncertain. Computational modeling can narrow the search by estimating the affinity and specificity of a given peptide in relation to a predetermined protein target. The predictive performance of computational models of interactions of intermediate-length peptides with proteins can be improved by taking into account the stochastic nature of the encounter and binding dynamics. A theoretical case is made for the hypothesis that, because of the flexibility of the peptide and the structural complexity of the target protein, interactions are best characterized by an ensemble of possible bound configurations rather than a single “lock and key” fit. A model incorporating these factors is proposed and evaluated. A comprehensive dataset of 3,924 peptide-protein interface structures was extracted from the Protein Data Bank (PDB) and descriptors were computed characterizing the geometry and energetics of each interface. The characteristics of these interfaces are shown to be generally consistent with the proposed model, and heuristics for design and selection of peptide ligands are derived. The curated and energy-minimized interface structure dataset and a relational database containing the detailed results of analysis and energy modeling are made publicly available via a web repository. A novel analytical technique based on the proposed theoretical model, Virtual Scanning Probe Mapping (VSPM), is implemented in software to analyze the interaction between a target protein of known structure and a peptide of specified sequence, producing a spatial map indicating the most likely peptide binding regions on the protein target. The resulting predictions are shown to be superior to those of two other published methods, and support the validity of the stochastic binding model.
ContributorsEmery, Jack Scott (Author) / Pizziconi, Vincent B (Thesis advisor) / Woodbury, Neal W (Thesis advisor) / Guilbeau, Eric J (Committee member) / Stafford, Phillip (Committee member) / Taylor, Thomas (Committee member) / Towe, Bruce C (Committee member) / Arizona State University (Publisher)
Created2010
Description
Bacteria with antibiotic resistance are becoming a growing concern as the number of infections they are causing continue to increase. Many potential solutions are being researched in order to combat these pathogens. One such microbe is Pseudomonas aeruginosa, which causes acute and chronic human infections. It frequently colonizes the lungs of cystic fibrosis patients and is deadly. For these reasons, P. aeruginosa has been heavily studied in order to determine a solution to antibiotic resistance. One possible solution is the development of synbodies, which have been developed at the Biodesign Institute at Arizona State University. Synbodies are constructed from peptides that have antibacterial activity and were determined to have specificity for a target bacterium. These synbodies were tested in this study to determine whether or not some of them are able to inhibit P. aeruginosa growth. P. aeruginosa can also form multicellular communities called biofilms and these are known to cause approximately 65% of all human infections. After conducting minimum inhibitory assays, the efficacy of certain peptides and synbodies against biofilm inhibition was assessed. A recent study has shown that low concentrations of a specific peptide can cause biofilm disruption, where the biofilm structure breaks apart and the cells within it disperse into the supernatant. Taking into account this study and peptide data regarding biofilm inhibition from Dr. Aurélie Crabbé’s lab, screened peptides were tested against biofilm to see if dispersion would occur.
ContributorsPatel, Justin Hemant (Author) / Diehnelt, Chris (Thesis director) / Stafford, Phillip (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2015-05
Description
Tactile and proprioceptive sensory feedback are the two sensory modalities that make up haptic sensation. The degree which these two sensory modalities are integrated together is not very well known. To investigate this issue a set of experiments were set into motion separating these sensory modalities and testing what happens when a person’s proprioceptive system is perturbed. A virtual reality system with haptic feedback along with a weighted object were utilized in a reach, grasp, and lift task. The subjects would lift two objects sequentially and try to judge which one was heavier. This project was split into three different experiments to measure the subject’s perception in different situations. The first experiment utilized the virtual reality system to measure the perception when the subject only has proprioceptive inputs. The second experiment would include the virtual reality system and the weighted object to act as a comparison to the first experiment with the additional tactile input. The third experiment would then add perturbations to the proprioceptive inputs through the virtual reality system to investigate how perception will change. Results from experiment 1 and 2 showed that subjects are almost just as accurate with weight discrimination even if they only have proprioceptive inputs however, subjects are much more consistent in their weight discrimination with both sensory modalities. Results from experiment 3 showed that subjective perception does change when the proprioception is perturbed but the magnitude of that change in perception depends on the perturbation performed.
ContributorsPerrine, Jacob (Author) / Santello, Marco (Thesis director) / Toma, Simone (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
Description
This research project investigated known and novel differential genetic variants and their associated molecular pathways involved in Type II diabetes mellitus for the purpose of improving diagnosis and treatment methods. The goal of this investigation was to 1) identify the genetic variants and SNPs in Type II diabetes to develop a gene regulatory pathway, and 2) utilize this pathway to determine suitable drug therapeutics for prevention and treatment. Using a Gene Set Enrichment Analysis (GSEA), a set of 1000 gene identifiers from a Mayo Clinic database was analyzed to determine the most significant genetic variants related to insulin signaling pathways involved in Type II Diabetes. The following genes were identified: NRAS, KRAS, PIK3CA, PDE3B, TSC1, AKT3, SOS1, NEU1, PRKAA2, AMPK, and ACC. In an extensive literature review and cross-analysis with Kegg and Reactome pathway databases, novel SNPs located on these gene variants were identified and used to determine suitable drug therapeutics for treatment. Overall, understanding how genetic mutations affect target gene function related to Type II Diabetes disease pathology is crucial to the development of effective diagnosis and treatment. This project provides new insight into the molecular basis of the Type II Diabetes, serving to help untangle the regulatory complexity of the disease and aid in the advancement of diagnosis and treatment. Keywords: Type II Diabetes mellitus, Gene Set Enrichment Analysis, genetic variants, KEGG Insulin Pathway, gene-regulatory pathway
ContributorsBucklin, Lindsay (Co-author) / Davis, Vanessa (Co-author) / Holechek, Susan (Thesis director) / Wang, Junwen (Committee member) / Nyarige, Verah (Committee member) / School of Human Evolution & Social Change (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
This research project investigated known and novel differential genetic variants and their associated molecular pathways involved in Type II diabetes mellitus for the purpose of improving diagnosis and treatment methods. The goal of this investigation was to 1) identify the genetic variants and SNPs in Type II diabetes to develop a gene regulatory pathway, and 2) utilize this pathway to determine suitable drug therapeutics for prevention and treatment. Using a Gene Set Enrichment Analysis (GSEA), a set of 1000 gene identifiers from a Mayo Clinic database was analyzed to determine the most significant genetic variants related to insulin signaling pathways involved in Type II Diabetes. The following genes were identified: NRAS, KRAS, PIK3CA, PDE3B, TSC1, AKT3, SOS1, NEU1, PRKAA2, AMPK, and ACC. In an extensive literature review and cross-analysis with Kegg and Reactome pathway databases, novel SNPs located on these gene variants were identified and used to determine suitable drug therapeutics for treatment. Overall, understanding how genetic mutations affect target gene function related to Type II Diabetes disease pathology is crucial to the development of effective diagnosis and treatment. This project provides new insight into the molecular basis of the Type II Diabetes, serving to help untangle the regulatory complexity of the disease and aid in the advancement of diagnosis and treatment.
ContributorsDavis, Vanessa Brooke (Co-author) / Bucklin, Lindsay (Co-author) / Holechek, Susan (Thesis director) / Wang, Junwen (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05