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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

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
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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

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
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Description
Multi-touch tablets and smart phones are now widely used in both workplace and consumer settings. Interacting with these devices requires hand and arm movements that are potentially complex and poorly understood. Experimental studies have revealed differences in performance that could potentially be associated with injury risk. However, underlying causes for

Multi-touch tablets and smart phones are now widely used in both workplace and consumer settings. Interacting with these devices requires hand and arm movements that are potentially complex and poorly understood. Experimental studies have revealed differences in performance that could potentially be associated with injury risk. However, underlying causes for performance differences are often difficult to identify. For example, many patterns of muscle activity can potentially result in similar behavioral output. Muscle activity is one factor contributing to forces in tissues that could contribute to injury. However, experimental measurements of muscle activity and force for humans are extremely challenging. Models of the musculoskeletal system can be used to make specific estimates of neuromuscular coordination and musculoskeletal forces. However, existing models cannot easily be used to describe complex, multi-finger gestures such as those used for multi-touch human computer interaction (HCI) tasks. We therefore seek to develop a dynamic musculoskeletal simulation capable of estimating internal musculoskeletal loading during multi-touch tasks involving multi digits of the hand, and use the simulation to better understand complex multi-touch and gestural movements, and potentially guide the design of technologies the reduce injury risk. To accomplish these, we focused on three specific tasks. First, we aimed at determining the optimal index finger muscle attachment points within the context of the established, validated OpenSim arm model using measured moment arm data taken from the literature. Second, we aimed at deriving moment arm values from experimentally-measured muscle attachments and using these values to determine muscle-tendon paths for both extrinsic and intrinsic muscles of middle, ring and little fingers. Finally, we aimed at exploring differences in hand muscle activation patterns during zooming and rotating tasks on the tablet computer in twelve subjects. Towards this end, our musculoskeletal hand model will help better address the neuromuscular coordination, safe gesture performance and internal loadings for multi-touch applications.
ContributorsYi, Chong-hwan (Author) / Jindrich, Devin L. (Thesis advisor) / Artemiadis, Panagiotis K. (Thesis advisor) / Phelan, Patrick (Committee member) / Santos, Veronica J. (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2014
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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

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
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Description
Understanding where our bodies are in space is imperative for motor control, particularly for actions such as goal-directed reaching. Multisensory integration is crucial for reducing uncertainty in arm position estimates. This dissertation examines time and frequency-domain correlates of visual-proprioceptive integration during an arm-position maintenance task. Neural recordings

Understanding where our bodies are in space is imperative for motor control, particularly for actions such as goal-directed reaching. Multisensory integration is crucial for reducing uncertainty in arm position estimates. This dissertation examines time and frequency-domain correlates of visual-proprioceptive integration during an arm-position maintenance task. Neural recordings were obtained from two different cortical areas as non-human primates performed a center-out reaching task in a virtual reality environment. Following a reach, animals maintained the end-point position of their arm under unimodal (proprioception only) and bimodal (proprioception and vision) conditions. In both areas, time domain and multi-taper spectral analysis methods were used to quantify changes in the spiking, local field potential (LFP), and spike-field coherence during arm-position maintenance.

In both areas, individual neurons were classified based on the spectrum of their spiking patterns. A large proportion of cells in the SPL that exhibited sensory condition-specific oscillatory spiking in the beta (13-30Hz) frequency band. Cells in the IPL typically had a more diverse mix of oscillatory and refractory spiking patterns during the task in response to changing sensory condition. Contrary to the assumptions made in many modelling studies, none of the cells exhibited Poisson-spiking statistics in SPL or IPL.

Evoked LFPs in both areas exhibited greater effects of target location than visual condition, though the evoked responses in the preferred reach direction were generally suppressed in the bimodal condition relative to the unimodal condition. Significant effects of target location on evoked responses were observed during the movement period of the task well.

In the frequency domain, LFP power in both cortical areas was enhanced in the beta band during the position estimation epoch of the task, indicating that LFP beta oscillations may be important for maintaining the ongoing state. This was particularly evident at the population level, with clear increase in alpha and beta power. Differences in spectral power between conditions also became apparent at the population level, with power during bimodal trials being suppressed relative to unimodal. The spike-field coherence showed confounding results in both the SPL and IPL, with no clear correlation between incidence of beta oscillations and significant beta coherence.
ContributorsVanGilder, Paul (Author) / Buneo, Christopher A (Thesis advisor) / Helms-Tillery, Stephen (Committee member) / Santello, Marco (Committee member) / Muthuswamy, Jit (Committee member) / Foldes, Stephen (Committee member) / Arizona State University (Publisher)
Created2017
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Description
The ultimate goal of human movement control research is to understand how natural movements performed in daily activities, are controlled. Natural movements require coordination of multiple degrees of freedom (DOF) of the arm. Here, patterns of arm joint control during daily functional tasks were examined, which are performed through rotation

The ultimate goal of human movement control research is to understand how natural movements performed in daily activities, are controlled. Natural movements require coordination of multiple degrees of freedom (DOF) of the arm. Here, patterns of arm joint control during daily functional tasks were examined, which are performed through rotation of the shoulder, elbow, and wrist with the use of seven DOF: shoulder flexion/extension, abduction/adduction, and internal/external rotation; elbow flexion/extension and pronation/supination; wrist flexion/extension and radial/ulnar deviation. Analyzed movements imitated two activities of daily living: combing the hair and turning the page in a book. Kinematic and kinetic analyses were conducted. The studied kinematic characteristics were displacements of the 7 DOF and contribution of each DOF to hand velocity. The kinetic analysis involved computation of 3-dimensional vectors of muscle torque (MT), interaction torque (IT), gravity torque (GT), and net torque (NT) at the shoulder, elbow, and wrist. Using a relationship NT = MT + GT + IT, the role of active control and the passive factors (gravitation and inter-segmental dynamics) in rotation of each joint was assessed by computing MT contribution (MTC) to NT. MTC was computed using the ratio of the signed MT projection on NT to NT magnitude. Despite the variety of joint movements required across the different tasks, 3 patterns of shoulder and elbow coordination prevailed in each movement: 1) active rotation of the shoulder and predominantly passive rotation of the elbow; 2) active rotation of the elbow and predominantly passive rotation of the shoulder; and 3) passive rotation of both joints. Analysis of wrist control suggested that MT mainly compensates for passive torque and provides adjustment of wrist motion according to requirements of both tasks. The 3 shoulder-elbow coordination patterns during which at least one joint moves largely passively represent joint control primitives underlying performance of well-learned arm movements, although these patterns may be less prevalent during non-habitual movements. The advantage of these control primitives is that they require minimal neural effort for joint coordination, and thus increase neural resources that can be used for cognitive tasks.
ContributorsMarshall, Dirk (Author) / Dounskaia, Natalia (Thesis advisor) / Schaefer, Sydney (Thesis advisor) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2018
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Description
The ultimate goal of human movement control research is to understand how natural movements performed in daily reaching activities, are controlled. Natural movements require coordination of multiple degrees of freedom (DOF) of the arm. Patterns of arm joint control were studied during daily functional tasks, which were performed through the

The ultimate goal of human movement control research is to understand how natural movements performed in daily reaching activities, are controlled. Natural movements require coordination of multiple degrees of freedom (DOF) of the arm. Patterns of arm joint control were studied during daily functional tasks, which were performed through the rotation of seven DOF in the arm. Analyzed movements which imitated the following 3 activities of daily living: moving an empty soda can from a table and placing it on a further position; placing the empty soda can from initial position at table to a position at shoulder level on a shelf; and placing the empty soda can from initial position at table to a position at eye level on a shelf. Kinematic and kinetic analyses were conducted for these three movements. The studied kinematic characteristics were: hand trajectory in the sagittal plane, displacements of the 7 DOF, and contribution of each DOF to hand velocity. The kinetic analysis involved computation of 3-dimensional vectors of muscle torque (MT), interaction torque (IT), gravity torque (GT), and net torque (NT) at the shoulder, elbow, and wrist. Using the relationship NT = MT + GT + IT, the role of active control and passive factors (gravitation and inter-segmental dynamics) in rotation of each joint by computing MT contribution (MTC) to NT was assessed. MTC was computed using the ratio of the signed MT projection on NT to NT magnitude. Despite a variety of joint movements available across the different tasks, 3 patterns of shoulder and elbow coordination prevailed in each movement: 1) active rotation of the shoulder and predominantly passive rotation of the elbow; 2) active rotation of the elbow and predominantly passive rotation of the shoulder; and 3) passive rotation of both joints. Analysis of wrist control suggested that MT mainly compensates for passive torque and provides adjustment of wrist motion according to requirements of each task. In conclusion, it was observed that the 3 shoulder-elbow coordination patterns (during which at least one joint moved) passively represented joint control primitives, underlying the performance of well-learned arm movements, although these patterns may be less prevalent during non-habitual movements.
ContributorsSansgiri, Dattaraj (Author) / Dounskaia, Natalia (Thesis advisor) / Schaefer, Sydney (Thesis advisor) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2018
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Description
The increasing usage of smart-phones and mobile devices in work environment and IT

industry has brought about unique set of challenges and opportunities. ARM architecture

in particular has evolved to a point where it supports implementations across wide spectrum

of performance points and ARM based tablets and smart-phones are in demand. The

enhancements to

The increasing usage of smart-phones and mobile devices in work environment and IT

industry has brought about unique set of challenges and opportunities. ARM architecture

in particular has evolved to a point where it supports implementations across wide spectrum

of performance points and ARM based tablets and smart-phones are in demand. The

enhancements to basic ARM RISC architecture allow ARM to have high performance,

small code size, low power consumption and small silicon area. Users want their devices to

perform many tasks such as read email, play games, and run other online applications and

organizations no longer desire to provision and maintain individual’s IT equipment. The

term BYOD (Bring Your Own Device) has come into being from demand of such a work

setup and is one of the motivation of this research work. It brings many opportunities such

as increased productivity and reduced costs and challenges such as secured data access,

data leakage and amount of control by the organization.

To provision such a framework we need to bridge the gap from both organizations side

and individuals point of view. Mobile device users face issue of application delivery on

multiple platforms. For instance having purchased many applications from one proprietary

application store, individuals may want to move them to a different platform/device but

currently this is not possible. Organizations face security issues in providing such a solution

as there are many potential threats from allowing BYOD work-style such as unauthorized

access to data, attacks from the devices within and outside the network.

ARM based Secure Mobile SDN framework will resolve these issues and enable employees

to consolidate both personal and business calls and mobile data access on a single device.

To address application delivery issue we are introducing KVM based virtualization that

will allow host OS to run multiple guest OS. To address the security problem we introduce

SDN environment where host would be running bridged network of guest OS using Open

vSwitch . This would allow a remote controller to monitor the state of guest OS for making

important control and traffic flow decisions based on the situation.
ContributorsChowdhary, Ankur (Author) / Huang, Dijiang (Thesis advisor) / Tong, Hanghang (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Humans have an inherent capability of performing highly dexterous and skillful tasks with their arms, involving maintaining posture, movement and interacting with the environment. The latter requires for them to control the dynamic characteristics of the upper limb musculoskeletal system. Inertia, damping and stiffness, a measure of mechanical impedance, gives

Humans have an inherent capability of performing highly dexterous and skillful tasks with their arms, involving maintaining posture, movement and interacting with the environment. The latter requires for them to control the dynamic characteristics of the upper limb musculoskeletal system. Inertia, damping and stiffness, a measure of mechanical impedance, gives a strong representation of these characteristics. Many previous studies have shown that the arm posture is a dominant factor for determining the end point impedance in a horizontal plane (transverse plane). The objective of this thesis is to characterize end point impedance of the human arm in the three dimensional (3D) space. Moreover, it investigates and models the control of the arm impedance due to increasing levels of muscle co-contraction. The characterization is done through experimental trials where human subjects maintained arm posture, while perturbed by a robot arm. Moreover, the subjects were asked to control the level of their arm muscles' co-contraction, using visual feedback of their muscles' activation, in order to investigate the effect of the muscle co-contraction on the arm impedance. The results of this study showed a very interesting, anisotropic increase of the arm stiffness due to muscle co-contraction. This can lead to very useful conclusions about the arm biomechanics as well as many implications for human motor control and more specifically the control of arm impedance through muscle co-contraction. The study finds implications for the EMG-based control of robots that physically interact with humans.
ContributorsPatel, Harshil Naresh (Author) / Artemiadis, Panagiotis (Thesis advisor) / Berman, Spring (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Real-Time Operating Systems are used in a variety of applications ranging from autonomous vehicles, flight controllers, and energy management systems to pacemakers, satellite tracking systems, amateur robotics and much more. It turns out that while general-purpose computers can perform tasks quite quickly, the execution time for various processes varies noticeably

Real-Time Operating Systems are used in a variety of applications ranging from autonomous vehicles, flight controllers, and energy management systems to pacemakers, satellite tracking systems, amateur robotics and much more. It turns out that while general-purpose computers can perform tasks quite quickly, the execution time for various processes varies noticeably between different executions. Execution time variation poses a big challenge for many computer-controlled systems that operate in the real-world such as robots, autonomous vehicles, drones, traffic signals, etc. The execution time variation matters in these systems since they must interact in the real world and perform actions at the proper times, and executing these tasks at other times can have varied effects ranging from a minor inconvenience to catastrophic failure. Many of these real-time systems are comprised of single board computers, such as a pacemaker. One single-board computer that is popular among hobbyists due to its form factor, cost, and performance is the Raspberry Pi, which uses an ARM-based processor. In order to provide a Real-Time Operating System for this single board computer this paper presents Jobbed, a single-core Real-Time Operating System which uses a fixed priority preemptive scheduler, targeted at the Raspberry Pi 2B. In this paper, we present the algorithmic structure behind this system and compare it to the Raspbian Operating System in an array of performance and behavioral tests targeted towards proper Real-Time Operating Systems.
ContributorsCunningham, Christian (Author) / Shrivastava, Aviral (Thesis director) / Vrudhula, Sarma (Committee member) / Barrett, The Honors College (Contributor) / Department of Physics (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05