Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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Description
Intracortical microstimulation (ICMS) within somatosensory cortex can produce artificial sensations including touch, pressure, and vibration. There is significant interest in using ICMS to provide sensory feedback for a prosthetic limb. In such a system, information recorded from sensors on the prosthetic would be translated into electrical stimulation and delivered directly to the brain, providing feedback about features of objects in contact with the prosthetic. To achieve this goal, multiple simultaneous streams of information will need to be encoded by ICMS in a manner that produces robust, reliable, and discriminable sensations. The first segment of this work focuses on the discriminability of sensations elicited by ICMS within somatosensory cortex. Stimulation on multiple single electrodes and near-simultaneous stimulation across multiple electrodes, driven by a multimodal tactile sensor, were both used in these experiments. A SynTouch BioTac sensor was moved across a flat surface in several directions, and a subset of the sensor's electrode impedance channels were used to drive multichannel ICMS in the somatosensory cortex of a non-human primate. The animal performed a behavioral task during this stimulation to indicate the discriminability of sensations evoked by the electrical stimulation. The animal's responses to ICMS were somewhat inconsistent across experimental sessions but indicated that discriminable sensations were evoked by both single and multichannel ICMS. The factors that affect the discriminability of stimulation-induced sensations are not well understood, in part because the relationship between ICMS and the neural activity it induces is poorly defined. The second component of this work was to develop computational models that describe the populations of neurons likely to be activated by ICMS. Models of several neurons were constructed, and their responses to ICMS were calculated. A three-dimensional cortical model was constructed using these cell models and used to identify the populations of neurons likely to be recruited by ICMS. Stimulation activated neurons in a sparse and discontinuous fashion; additionally, the type, number, and location of neurons likely to be activated by stimulation varied with electrode depth.
ContributorsOverstreet, Cynthia K (Author) / Helms Tillery, Stephen I (Thesis advisor) / Santos, Veronica (Committee member) / Buneo, Christopher (Committee member) / Otto, Kevin (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2013
Description
In order to successfully implement a neural prosthetic system, it is necessary to understand the control of limb movements and the representation of body position in the nervous system. As this development process continues, it is becoming increasingly important to understand the way multiple sensory modalities are used in limb representation. In a previous study, Shi et al. (2013) examined the multimodal basis of limb position in the superior parietal lobule (SPL) as monkeys reached to and held their arm at various target locations in a frontal plane. Visual feedback was withheld in half the trials, though non-visual (i.e. somatic) feedback was available in all trials. Previous analysis showed that some of the neurons were tuned to limb position and that some neurons had their response modulated by the presence or absence of visual feedback. This modulation manifested in decreases in firing rate variability in the vision condition as compared to nonvision. The decreases in firing rate variability, as shown through decreases in both the Fano factor of spike counts and the coefficient of variation of the inter-spike intervals, suggested that changes were taking place in both trial-by-trial and intra-trial variability. I sought to further probe the source of the change in intra-trial variability through spectral analysis. It was hypothesized that the presence of temporal structure in the vision condition would account for a regularity in firing that would have decreased intra-trial variability. While no peaks were apparent in the spectra, differences in spectral power between visual conditions were found. These differences are suggestive of unique temporal spiking patterns at the individual neuron level that may be influential at the population level.
ContributorsDyson, Keith (Author) / Buneo, Christopher A (Thesis advisor) / Helms-Tillery, Stephen I (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2013
Description
Reaching movements are subject to noise in both the planning and execution phases of movement production. Although the effects of these noise sources in estimating and/or controlling endpoint position have been examined in many studies, the independent effects of limb configuration on endpoint variability have been largely ignored. The present study investigated the effects of arm configuration on the interaction between planning noise and execution noise. Subjects performed reaching movements to three targets located in a frontal plane. At the starting position, subjects matched one of two desired arm configuration 'templates' namely "adducted" and "abducted". These arm configurations were obtained by rotations along the shoulder-hand axis, thereby maintaining endpoint position. Visual feedback of the hand was varied from trial to trial, thereby increasing uncertainty in movement planning and execution. It was hypothesized that 1) pattern of endpoint variability would be dependent on arm configuration and 2) that these differences would be most apparent in conditions without visual feedback. It was found that there were differences in endpoint variability between arm configurations in both visual conditions, but these differences were much larger when visual feedback was withheld. The overall results suggest that patterns of endpoint variability are highly dependent on arm configuration, particularly in the absence of visual feedback. This suggests that in the presence of vision, movement planning in 3D space is performed using coordinates that are largely arm configuration independent (i.e. extrinsic coordinates). In contrast, in the absence of vision, movement planning in 3D space reflects a substantial contribution of intrinsic coordinates.
ContributorsLakshmi Narayanan, Kishor (Author) / Buneo, Christopher (Thesis advisor) / Santello, Marco (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Myoelectric control is lled with potential to signicantly change human-robot interaction.
Humans desire compliant robots to safely interact in dynamic environments
associated with daily activities. As surface electromyography non-invasively measures
limb motion intent and correlates with joint stiness during co-contractions,
it has been identied as a candidate for naturally controlling such robots. However,
state-of-the-art myoelectric interfaces have struggled to achieve both enhanced
functionality and long-term reliability. As demands in myoelectric interfaces trend
toward simultaneous and proportional control of compliant robots, robust processing
of multi-muscle coordinations, or synergies, plays a larger role in the success of the
control scheme. This dissertation presents a framework enhancing the utility of myoelectric
interfaces by exploiting motor skill learning and
exible muscle synergies for
reliable long-term simultaneous and proportional control of multifunctional compliant
robots. The interface is learned as a new motor skill specic to the controller,
providing long-term performance enhancements without requiring any retraining or
recalibration of the system. Moreover, the framework oers control of both motion
and stiness simultaneously for intuitive and compliant human-robot interaction. The
framework is validated through a series of experiments characterizing motor learning
properties and demonstrating control capabilities not seen previously in the literature.
The results validate the approach as a viable option to remove the trade-o
between functionality and reliability that have hindered state-of-the-art myoelectric
interfaces. Thus, this research contributes to the expansion and enhancement of myoelectric
controlled applications beyond commonly perceived anthropomorphic and
\intuitive control" constraints and into more advanced robotic systems designed for
everyday tasks.
Humans desire compliant robots to safely interact in dynamic environments
associated with daily activities. As surface electromyography non-invasively measures
limb motion intent and correlates with joint stiness during co-contractions,
it has been identied as a candidate for naturally controlling such robots. However,
state-of-the-art myoelectric interfaces have struggled to achieve both enhanced
functionality and long-term reliability. As demands in myoelectric interfaces trend
toward simultaneous and proportional control of compliant robots, robust processing
of multi-muscle coordinations, or synergies, plays a larger role in the success of the
control scheme. This dissertation presents a framework enhancing the utility of myoelectric
interfaces by exploiting motor skill learning and
exible muscle synergies for
reliable long-term simultaneous and proportional control of multifunctional compliant
robots. The interface is learned as a new motor skill specic to the controller,
providing long-term performance enhancements without requiring any retraining or
recalibration of the system. Moreover, the framework oers control of both motion
and stiness simultaneously for intuitive and compliant human-robot interaction. The
framework is validated through a series of experiments characterizing motor learning
properties and demonstrating control capabilities not seen previously in the literature.
The results validate the approach as a viable option to remove the trade-o
between functionality and reliability that have hindered state-of-the-art myoelectric
interfaces. Thus, this research contributes to the expansion and enhancement of myoelectric
controlled applications beyond commonly perceived anthropomorphic and
\intuitive control" constraints and into more advanced robotic systems designed for
everyday tasks.
ContributorsIson, Mark (Author) / Artemiadis, Panagiotis (Thesis advisor) / Santello, Marco (Committee member) / Greger, Bradley (Committee member) / Berman, Spring (Committee member) / Sugar, Thomas (Committee member) / Fainekos, Georgios (Committee member) / Arizona State University (Publisher)
Created2015
Description
Peripheral Vascular Disease (PVD) is a debilitating chronic disease of the lower extremities particularly affecting older adults and diabetics. It results in reduction of the blood flow to peripheral tissue and sometimes causing tissue damage such that PVD patients suffer from pain in the lower legs, thigh and buttocks after activities. Electrical neurostimulation based on the "Gate Theory of Pain" is a known to way to reduce pain but current devices to do this are bulky and not well suited to implantation in peripheral tissues. There is also an increased risk associated with surgery which limits the use of these devices. This research has designed and constructed wireless ultrasound powered microstimulators that are much smaller and injectable and so involve less implantation trauma. These devices are small enough to fit through an 18 gauge syringe needle increasing their potential for clinical use. These piezoelectric microdevices convert mechanical energy into electrical energy that then is used to block pain. The design and performance of these miniaturized devices was modeled by computer while constructed devices were evaluated in animal experiments. The devices are capable of producing 500ms pulses with an intensity of 2 mA into a 2 kilo-ohms load. Using the rat as an animal model, a series of experiments were conducted to evaluate the in-vivo performance of the devices.
ContributorsZong, Xi (Author) / Towe, Bruce (Thesis advisor) / Kleim, Jeffrey (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2014
Description
An accurate sense of upper limb position is crucial to reaching movements where sensory information about upper limb position and target location is combined to specify critical features of the movement plan. This dissertation was dedicated to studying the mechanisms of how the brain estimates the limb position in space and the consequences of misestimation of limb position on movements. Two independent but related studies were performed. The first involved characterizing the neural mechanisms of limb position estimation in the non-human primate brain. Single unit recordings were obtained in area 5 of the posterior parietal cortex in order to examine the role of this area in estimating limb position based on visual and somatic signals (proprioceptive, efference copy). When examined individually, many area 5 neurons were tuned to the position of the limb in the workspace but very few neurons were modulated by visual feedback. At the population level however decoding of limb position was somewhat more accurate when visual feedback was provided. These findings support a role for area 5 in limb position estimation but also suggest that visual signals regarding limb position are only weakly represented in this area, and only at the population level. The second part of this dissertation focused on the consequences of misestimation of limb position for movement production. It is well known that limb movements are inherently variable. This variability could be the result of noise arising at one or more stages of movement production. Here we used biomechanical modeling and simulation techniques to characterize movement variability resulting from noise in estimating limb position ('sensing noise') and in planning required movement vectors ('planning noise'), and compared that to the variability expected due to noise in movement execution. We found that the effects of sensing and planning related noise on movement variability were dependent upon both the planned movement direction and the initial configuration of the arm and were different in many respects from the effects of execution noise.
ContributorsShi, Ying (Author) / Buneo, Christopher A (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Santello, Marco (Committee member) / He, Jiping (Committee member) / Santos, Veronica (Committee member) / Arizona State University (Publisher)
Created2011
Description
The ability to plan, execute, and control goal oriented reaching and grasping movements is among the most essential functions of the brain. Yet, these movements are inherently variable; a result of the noise pervading the neural signals underlying sensorimotor processing. The specific influences and interactions of these noise processes remain unclear. Thus several studies have been performed to elucidate the role and influence of sensorimotor noise on movement variability. The first study focuses on sensory integration and movement planning across the reaching workspace. An experiment was designed to examine the relative contributions of vision and proprioception to movement planning by measuring the rotation of the initial movement direction induced by a perturbation of the visual feedback prior to movement onset. The results suggest that contribution of vision was relatively consistent across the evaluated workspace depths; however, the influence of vision differed between the vertical and later axes indicate that additional factors beyond vision and proprioception influence movement planning of 3-dimensional movements. If the first study investigated the role of noise in sensorimotor integration, the second and third studies investigate relative influence of sensorimotor noise on reaching performance. Specifically, they evaluate how the characteristics of neural processing that underlie movement planning and execution manifest in movement variability during natural reaching. Subjects performed reaching movements with and without visual feedback throughout the movement and the patterns of endpoint variability were compared across movement directions. The results of these studies suggest a primary role of visual feedback noise in shaping patterns of variability and in determining the relative influence of planning and execution related noise sources. The final work considers a computational approach to characterizing how sensorimotor processes interact to shape movement variability. A model of multi-modal feedback control was developed to simulate the interaction of planning and execution noise on reaching variability. The model predictions suggest that anisotropic properties of feedback noise significantly affect the relative influence of planning and execution noise on patterns of reaching variability.
ContributorsApker, Gregory Allen (Author) / Buneo, Christopher A (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Santello, Marco (Committee member) / Santos, Veronica (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2012
Description
Approximately 1.7 million people in the United States are living with limb loss and are in need of more sophisticated devices that better mimic human function. In the Human Machine Integration Laboratory, a powered, transtibial prosthetic ankle was designed and build that allows a person to regain ankle function with improved ankle kinematics and kinetics. The ankle allows a person to walk normally and up and down stairs, but volitional control is still an issue. This research tackled the problem of giving the user more control over the prosthetic ankle using a force/torque circuit. When the user presses against a force/torque sensor located inside the socket the prosthetic foot plantar flexes or moves downward. This will help the user add additional push-off force when walking up slopes or stairs. It also gives the user a sense of control over the device.
ContributorsFronczyk, Adam (Author) / Sugar, Thomas G. (Thesis advisor) / Helms-Tillery, Stephen (Thesis advisor) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2012
Description
Effective tactile sensing in prosthetic and robotic hands is crucial for improving the functionality of such hands and enhancing the user's experience. Thus, improving the range of tactile sensing capabilities is essential for developing versatile artificial hands. Multimodal tactile sensors called BioTacs, which include a hydrophone and a force electrode array, were used to understand how grip force, contact angle, object texture, and slip direction may be encoded in the sensor data. Findings show that slip induced under conditions of high contact angles and grip forces resulted in significant changes in both AC and DC pressure magnitude and rate of change in pressure. Slip induced under conditions of low contact angles and grip forces resulted in significant changes in the rate of change in electrode impedance. Slip in the distal direction of a precision grip caused significant changes in pressure magnitude and rate of change in pressure, while slip in the radial direction of the wrist caused significant changes in the rate of change in electrode impedance. A strong relationship was established between slip direction and the rate of change in ratios of electrode impedance for radial and ulnar slip relative to the wrist. Consequently, establishing multiple thresholds or establishing a multivariate model may be a useful method for detecting and characterizing slip. Detecting slip for low contact angles could be done by monitoring electrode data, while detecting slip for high contact angles could be done by monitoring pressure data. Predicting slip in the distal direction could be done by monitoring pressure data, while predicting slip in the radial and ulnar directions could be done by monitoring electrode data.
ContributorsHsia, Albert (Author) / Santos, Veronica J (Thesis advisor) / Santello, Marco (Committee member) / Helms Tillery, Stephen I (Committee member) / Arizona State University (Publisher)
Created2012
Description
Lower-limb prosthesis users have commonly-recognized deficits in gait and posture control. However, existing methods in balance and mobility analysis fail to provide sufficient sensitivity to detect changes in prosthesis users' postural control and mobility in response to clinical intervention or experimental manipulations and often fail to detect differences between prosthesis users and non-amputee control subjects. This lack of sensitivity limits the ability of clinicians to make informed clinical decisions and presents challenges with insurance reimbursement for comprehensive clinical care and advanced prosthetic devices. These issues have directly impacted clinical care by restricting device options, increasing financial burden on clinics, and limiting support for research and development. This work aims to establish experimental methods and outcome measures that are more sensitive than traditional methods to balance and mobility changes in prosthesis users. Methods and analysis techniques were developed to probe aspects of balance and mobility control that may be specifically impacted by use of a prosthesis and present challenges similar to those experienced in daily life that could improve the detection of balance and mobility changes. Using the framework of cognitive resource allocation and dual-tasking, this work identified unique characteristics of prosthesis users’ postural control and developed sensitive measures of gait variability. The results also provide broader insight into dual-task analysis and the motor-cognitive response to demanding conditions. Specifically, this work identified altered motor behavior in prosthesis users and high cognitive demand of using a prosthesis. The residual standard deviation method was developed and demonstrated to be more effective than traditional gait variability measures at detecting the impact of dual-tasking. Additionally, spectral analysis of the center of pressure while standing identified altered somatosensory control in prosthesis users. These findings provide a new understanding of prosthetic use and new, highly sensitive techniques to assess balance and mobility in prosthesis users.
ContributorsHoward, Charla Lindley (Author) / Abbas, James (Thesis advisor) / Buneo, Christopher (Committee member) / Lynskey, Jim (Committee member) / Santello, Marco (Committee member) / Artemiadis, Panagiotis (Committee member) / Arizona State University (Publisher)
Created2017