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Description
Humans are capable of transferring learning for anticipatory control of dexterous object manipulation despite changes in degrees-of-freedom (DoF), i.e., switching from lifting an object with two fingers to lifting the same object with three fingers. However, the role that tactile information plays in this transfer of learning is unknown. In

Humans are capable of transferring learning for anticipatory control of dexterous object manipulation despite changes in degrees-of-freedom (DoF), i.e., switching from lifting an object with two fingers to lifting the same object with three fingers. However, the role that tactile information plays in this transfer of learning is unknown. In this study, subjects lifted an L-shaped object with two fingers (2-DoF), and then lifted the object with three fingers (3-DoF). The subjects were divided into two groups--one group performed the task wearing a glove (to reduce tactile sensibility) upon the switch to 3-DoF (glove group), while the other group did not wear the glove (control group). Compensatory moment (torque) was used as a measure to determine how well the subject could minimize the tilt of the object following the switch from 2-DoF to 3-DoF. Upon the switch to 3-DoF, subjects wearing the glove generated a compensatory moment (Mcom) that had a significantly higher error than the average of the last five trials at the end of the 3-DoF block (p = 0.012), while the control subjects did not demonstrate a significant difference in Mcom. Additional effects of the reduction in tactile sensibility were: (1) the grip force for the group of subjects wearing the glove was significantly higher in the 3-DoF trials compared to the 2-DoF trials (p = 0.014), while the grip force of the control subjects was not significantly different; (2) the difference in centers of pressure between the thumb and fingers (ΔCoP) significantly increased in the 3-DoF block for the group of subjects wearing the glove, while the ΔCoP of the control subjects was not significantly different; (3) lastly, the control subjects demonstrated a greater increase in lift force than the group of subjects wearing the glove (though results were not significant). Combined together, these results suggest different force modulation strategies are used depending on the amount of tactile feedback that is available to the subject. Therefore, reduction of tactile sensibility has important effects on subjects' ability to transfer learned manipulation across different DoF contexts.
ContributorsGaw, Nathan (Author) / Helms Tillery, Stephen (Thesis advisor) / Santello, Marco (Committee member) / Kleim, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Situations of sensory overload are steadily becoming more frequent as the ubiquity of technology approaches reality--particularly with the advent of socio-communicative smartphone applications, and pervasive, high speed wireless networks. Although the ease of accessing information has improved our communication effectiveness and efficiency, our visual and auditory modalities--those modalities that today's

Situations of sensory overload are steadily becoming more frequent as the ubiquity of technology approaches reality--particularly with the advent of socio-communicative smartphone applications, and pervasive, high speed wireless networks. Although the ease of accessing information has improved our communication effectiveness and efficiency, our visual and auditory modalities--those modalities that today's computerized devices and displays largely engage--have become overloaded, creating possibilities for distractions, delays and high cognitive load; which in turn can lead to a loss of situational awareness, increasing chances for life threatening situations such as texting while driving. Surprisingly, alternative modalities for information delivery have seen little exploration. Touch, in particular, is a promising candidate given that it is our largest sensory organ with impressive spatial and temporal acuity. Although some approaches have been proposed for touch-based information delivery, they are not without limitations including high learning curves, limited applicability and/or limited expression. This is largely due to the lack of a versatile, comprehensive design theory--specifically, a theory that addresses the design of touch-based building blocks for expandable, efficient, rich and robust touch languages that are easy to learn and use. Moreover, beyond design, there is a lack of implementation and evaluation theories for such languages. To overcome these limitations, a unified, theoretical framework, inspired by natural, spoken language, is proposed called Somatic ABC's for Articulating (designing), Building (developing) and Confirming (evaluating) touch-based languages. To evaluate the usefulness of Somatic ABC's, its design, implementation and evaluation theories were applied to create communication languages for two very unique application areas: audio described movies and motor learning. These applications were chosen as they presented opportunities for complementing communication by offloading information, typically conveyed visually and/or aurally, to the skin. For both studies, it was found that Somatic ABC's aided the design, development and evaluation of rich somatic languages with distinct and natural communication units.
ContributorsMcDaniel, Troy Lee (Author) / Panchanathan, Sethuraman (Thesis advisor) / Davulcu, Hasan (Committee member) / Li, Baoxin (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2012
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Description
In the search for chemical biosensors designed for patient-based physiological applications, non-invasive diagnostic approaches continue to have value. The work described in this thesis builds upon previous breath analysis studies. In particular, it seeks to assess the adsorptive mechanisms active in both acetone and ethanol biosensors designed for

In the search for chemical biosensors designed for patient-based physiological applications, non-invasive diagnostic approaches continue to have value. The work described in this thesis builds upon previous breath analysis studies. In particular, it seeks to assess the adsorptive mechanisms active in both acetone and ethanol biosensors designed for breath analysis. The thermoelectric biosensors under investigation were constructed using a thermopile for transduction and four different materials for biorecognition. The analytes, acetone and ethanol, were evaluated under dry-air and humidified-air conditions. The biosensor response to acetone concentration was found to be both repeatable and linear, while the sensor response to ethanol presence was also found to be repeatable. The different biorecognition materials produced discernible thermoelectric responses that were characteristic for each analyte. The sensor output data is presented in this report. Additionally, the results were evaluated against a mathematical model for further analysis. Ultimately, a thermoelectric biosensor based upon adsorption chemistry was developed and characterized. Additional work is needed to characterize the physicochemical action mechanism.
ContributorsWilson, Kimberly (Author) / Guilbeau, Eric (Thesis advisor) / Pizziconi, Vincent (Thesis advisor) / LaBelle, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Bioscience High School, a small magnet high school located in Downtown Phoenix and a STEAM (Science, Technology, Engineering, Arts, Math) focused school, has been pushing to establish a computer science curriculum for all of their students from freshman to senior year. The school's Mision (Mission and Vision) is to: "..provide

Bioscience High School, a small magnet high school located in Downtown Phoenix and a STEAM (Science, Technology, Engineering, Arts, Math) focused school, has been pushing to establish a computer science curriculum for all of their students from freshman to senior year. The school's Mision (Mission and Vision) is to: "..provide a rigorous, collaborative, and relevant academic program emphasizing an innovative, problem-based curriculum that develops literacy in the sciences, mathematics, and the arts, thus cultivating critical thinkers, creative problem-solvers, and compassionate citizens, who are able to thrive in our increasingly complex and technological communities." Computational thinking is an important part in developing a future problem solver Bioscience High School is looking to produce. Bioscience High School is unique in the fact that every student has a computer available for him or her to use. Therefore, it makes complete sense for the school to add computer science to their curriculum because one of the school's goals is to be able to utilize their resources to their full potential. However, the school's attempt at computer science integration falls short due to the lack of expertise amongst the math and science teachers. The lack of training and support has postponed the development of the program and they are desperately in need of someone with expertise in the field to help reboot the program. As a result, I've decided to create a course that is focused on teaching students the concepts of computational thinking and its application through Scratch and Arduino programming.
ContributorsLiu, Deming (Author) / Meuth, Ryan (Thesis director) / Nakamura, Mutsumi (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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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

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
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Description
The American Diabetes Association reports that diabetes costs $322 billion annually and affects 29.1 million Americans. The high out-of-pocket cost of managing diabetes can lead to noncompliance causing serious and expensive complications. There is a large market potential for a more cost-effective alternative to the current market standard of screen-printed

The American Diabetes Association reports that diabetes costs $322 billion annually and affects 29.1 million Americans. The high out-of-pocket cost of managing diabetes can lead to noncompliance causing serious and expensive complications. There is a large market potential for a more cost-effective alternative to the current market standard of screen-printed self-monitoring blood glucose (SMBG) strips. Additive manufacturing, specifically 3D printing, is a developing field that is growing in popularity and functionality. 3D printers are now being used in a variety of applications from consumer goods to medical devices. Healthcare delivery will change as the availability of 3D printers expands into patient homes, which will create alternative and more cost-effective methods of monitoring and managing diseases, such as diabetes. 3D printing technology could transform this expensive industry. A 3D printed sensor was designed to have similar dimensions and features to the SMBG strips to comply with current manufacturing standards. To make the sensor electrically active, various conductive filaments were tested and the conductive graphene filament was determined to be the best material for the sensor. Experiments were conducted to determine the optimal print settings for printing this filament onto a mylar substrate, the industry standard. The reagents used include a mixture of a ferricyanide redox mediator and flavin adenine dinucleotide dependent glucose dehydrogenase. With these materials, each sensor only costs $0.40 to print and use. Before testing the 3D printed sensor, a suitable design, voltage range, and redox probe concentration were determined. Experiments demonstrated that this novel 3D printed sensor can accurately correlate current output to glucose concentration. It was verified that the sensor can accurately detect glucose levels from 25 mg/dL to 400 mg/dL, with an R2 correlation value as high as 0.97, which was critical as it covered hypoglycemic to hyperglycemic levels. This demonstrated that a 3D-printed sensor was created that had characteristics that are suitable for clinical use. This will allow diabetics to print their own test strips at home at a much lower cost compared to SMBG strips, which will reduce noncompliance due to the high cost of testing. In the future, this technology could be applied to additional biomarkers to measure and monitor other diseases.
ContributorsAdams, Anngela (Author) / LaBelle, Jeffrey (Thesis advisor) / Pizziconi, Vincent (Committee member) / Abbas, James (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Millions of individuals suffer from gait impairments due to stroke or other neurological disorders. A primary goal of patients is to walk independently, but most patients only achieve a poor functional outcome five years after injury. Despite the growing interest in using robotic devices for rehabilitation of sensorimotor

Millions of individuals suffer from gait impairments due to stroke or other neurological disorders. A primary goal of patients is to walk independently, but most patients only achieve a poor functional outcome five years after injury. Despite the growing interest in using robotic devices for rehabilitation of sensorimotor function, state-of-the-art robotic interventions in gait therapy have not resulted in improved outcomes when compared to traditional treadmill-based therapy. Because bipedal walking requires neural coupling and dynamic interactions between the legs, a fundamental understanding of the sensorimotor mechanisms of inter-leg coordination during walking is needed to inform robotic interventions in gait therapy. This dissertation presents a systematic exploration of sensorimotor mechanisms of inter-leg coordination by studying the effect of unilateral perturbations of the walking surface stiffness on contralateral muscle activation in healthy populations. An analysis of the contribution of several sensory modalities to the muscle activation of the opposite leg provides new insight into the sensorimotor control mechanisms utilized in human walking, including the role of supra-spinal neural circuits in inter-leg coordination. Based on these insights, a model is created which relates the unilateral deflection of the walking surface to the resulting neuromuscular activation in the opposite leg. Additionally, case studies with hemiplegic walkers indicate the existence of the observed mechanism in neurologically impaired walkers. The results of this dissertation suggest a novel approach to gait therapy for hemiplegic patients in which desired muscle activity is evoked in the impaired leg by only interacting with the healthy leg. One of the most significant advantages of this approach over current rehabilitation protocols is the safety of the patient since there is no direct manipulation of the impaired leg. Therefore, the methods and results presented in this dissertation represent a potential paradigm shift in robot-assisted gait therapy.
ContributorsSkidmore, Jeffrey Alan (Author) / Artemiadis, Panagiotis (Thesis advisor) / Santello, Marco (Committee member) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2017
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Description
The human hand comprises complex sensorimotor functions that can be impaired by neurological diseases and traumatic injuries. Effective rehabilitation can bring the impaired hand back to a functional state because of the plasticity of the central nervous system to relearn and remodel the lost synapses in the brain. Current rehabilitation

The human hand comprises complex sensorimotor functions that can be impaired by neurological diseases and traumatic injuries. Effective rehabilitation can bring the impaired hand back to a functional state because of the plasticity of the central nervous system to relearn and remodel the lost synapses in the brain. Current rehabilitation therapies focus on strengthening motor skills, such as grasping, employ multiple objects of varying stiffness and devices that are bulky, costly, and have limited range of stiffness due to the rigid mechanisms employed in their variable stiffness actuators. This research project presents a portable cost-effective soft robotic haptic device with a broad stiffness range that is adjustable and can be utilized in both clinical and home settings. The device eliminates the need for multiple objects by employing a pneumatic soft structure made with highly compliant materials that act as the actuator as well as the structure of the haptic interface. It is made with interchangeable soft elastomeric sleeves that can be customized to include materials of varying stiffness to increase or decrease the stiffness range. The device is fabricated using existing 3D printing technologies, and polymer molding and casting techniques, thus keeping the cost low and throughput high. The haptic interface is linked to either an open-loop system that allows for an increased pressure during usage or closed-loop system that provides pressure regulation in accordance with the stiffness the user specifies. A preliminary evaluation is performed to characterize the effective controllable region of variance in stiffness. Results indicate that the region of controllable stiffness was in the center of the device, where the stiffness appeared to plateau with each increase in pressure. The two control systems are tested to derive relationships between internal pressure, grasping force exertion on the surface, and displacement using multiple probing points on the haptic device. Additional quantitative evaluation is performed with study participants and juxtaposed to a qualitative analysis to ensure adequate perception in compliance variance. Finally, a qualitative evaluation showed that greater than 60% of the trials resulted in the correct perception of stiffness in the haptic device.
ContributorsSebastian, Frederick (Author) / Polygerinos, Panagiotis (Thesis advisor) / Santello, Marco (Committee member) / Fu, Qiushi (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Stroke accounts for high rates of mortality and disability in the United States. It levies great economic burden on the affected subjects, their family and the society at large. Motor impairments after stroke mainly manifest themselves as hemiplegia or hemiparesis in the upper and lower limbs. Motor recovery is highly

Stroke accounts for high rates of mortality and disability in the United States. It levies great economic burden on the affected subjects, their family and the society at large. Motor impairments after stroke mainly manifest themselves as hemiplegia or hemiparesis in the upper and lower limbs. Motor recovery is highly variable but can be enhanced through motor rehabilitation with sufficient movement repetition and intensity. Cost effective assistive devices that can augment therapy by increasing movement repetition both at home and in the clinic may facilitate recovery. This thesis aims to develop a Smart Glove that can enhance motor recovery by providing feedback to both the therapist and the patient on the number of hand movements (wrist and finger extensions) performed during therapy. The design implements resistive flex sensors for detecting the extensions and processes the information using the Lightblue bean microcontroller mounted on the wrist. Communication between the processing unit and display module is wireless and executes Bluetooth 4.0 communication protocol. The capacity for the glove to measure and record hand movements was tested on three stroke and one traumatic brain injured patient while performing a box and blocks test. During testing many design flaws were noted and several were adapted during testing to improve the function of the glove. Results of the testing showed that the glove could detect wrist and finger extensions but that the sensitivity had to be calibrated for each patient. It also allowed both the therapist and patient to know whether the patient was actually performing the task in the manner requested by the therapist. Further work will reveal whether this feedback can enhance recovery of hand function in neurologically impaired patients.
ContributorsSasidharan, Smrithi (Author) / Kleim, Jeffrey A. (Thesis advisor) / Santello, Marco (Committee member) / Buneo, Christopher A. (Committee member) / Arizona State University (Publisher)
Created2015