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ASU Electronic Theses and Dissertations


This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.




In the last 15 years, there has been a significant increase in the number of motor neural prostheses used for restoring limb function lost due to neurological disorders or accidents. The aim of this technology is to enable patients to control a motor prosthesis using their residual neural pathways (central or peripheral). Recent studies in non-human primates and humans have shown the possibility of controlling a prosthesis for accomplishing varied tasks such as self-feeding, typing, reaching, grasping, and performing fine dexterous movements. A neural decoding system comprises mainly of three components: (i) sensors to record neural signals, (ii) an algorithm …

Contributors
Padmanaban, Subash, Greger, Bradley, Santello, Marco, et al.
Created Date
2017

Object manipulation is a common sensorimotor task that humans perform to interact with the physical world. The first aim of this dissertation was to characterize and identify the role of feedback and feedforward mechanisms for force control in object manipulation by introducing a new feature based on force trajectories to quantify the interaction between feedback- and feedforward control. This feature was applied on two grasp contexts: grasping the object at either (1) predetermined or (2) self-selected grasp locations (“constrained” and “unconstrained”, respectively), where unconstrained grasping is thought to involve feedback-driven force corrections to a greater extent than constrained grasping. This …

Contributors
Mojtahedi, Keivan, Santello, Marco, Greger, Bradley, et al.
Created Date
2017

Robust and stable decoding of neural signals is imperative for implementing a useful neuroprosthesis capable of carrying out dexterous tasks. A nonhuman primate (NHP) was trained to perform combined flexions of the thumb, index and middle fingers in addition to individual flexions and extensions of the same digits. An array of microelectrodes was implanted in the hand area of the motor cortex of the NHP and used to record action potentials during finger movements. A Support Vector Machine (SVM) was used to classify which finger movement the NHP was making based upon action potential firing rates. The effect of four …

Contributors
Padmanaban, Subash, Greger, Bradley, Santello, Marco, et al.
Created Date
2015

Prosthetic users abandon devices due to difficulties performing tasks without proper graded or interpretable feedback. The inability to adequately detect and correct error of the device leads to failure and frustration. In advanced prostheses, peripheral nerve stimulation can be used to deliver sensations, but standard schemes used in sensorized prosthetic systems induce percepts inconsistent with natural sensations, providing limited benefit. Recent uses of time varying stimulation strategies appear to produce more practical sensations, but without a clear path to pursue improvements. This dissertation examines the use of physiologically based stimulation strategies to elicit sensations that are more readily interpretable. A …

Contributors
Tanner, Justin Cody, Helms Tillery, Stephen I, Santos, Veronica J, et al.
Created Date
2017

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 …

Contributors
Ison, Mark, Artemiadis, Panagiotis, Santello, Marco, et al.
Created Date
2015

Neural interfacing applications have advanced in complexity, with needs for increasingly high degrees of freedom in prosthetic device control, sharper discrimination in sensory percepts in bidirectional interfaces, and more precise localization of functional connectivity in the brain. As such, there is a growing need for reliable neurophysiological recordings at a fine spatial scale matching that of cortical columnar processing. Penetrating microelectrodes provide localization sufficient to isolate action potential (AP) waveforms, but often suffer from recorded signal deterioration linked to foreign body response. Micro-Electrocorticography (μECoG) surface electrodes elicit lower foreign body response and show greater chronic stability of recorded signals, though …

Contributors
Barton, Cody David, Greger, Bradley, Greger, Bradley, et al.
Created Date
2018