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- Genre: Doctoral Dissertation
Description
The efficacy of deep brain stimulation (DBS) in Parkinson's disease (PD) has been convincingly demonstrated in studies that compare motor performance with and without stimulation, but characterization of performance at intermediate stimulation amplitudes has been limited. This study investigated the effects of changing DBS amplitude in order to assess dose-response characteristics, inter-subject variability, consistency of effect across outcome measures, and day-to-day variability. Eight subjects with PD and bilateral DBS systems were evaluated at their clinically determined stimulation (CDS) and at three reduced amplitude conditions: approximately 70%, 30%, and 0% of the CDS (MOD, LOW, and OFF, respectively). Overall symptom severity and performance on a battery of motor tasks - gait, postural control, single-joint flexion-extension, postural tremor, and tapping - were assessed at each condition using the motor section of the Unified Parkinson's Disease Rating Scale (UPDRS-III) and quantitative measures. Data were analyzed to determine whether subjects demonstrated a threshold response (one decrement in stimulation resulted in ≥ 70% of the maximum change) or a graded response to reduced stimulation. Day-to-day variability was assessed using the CDS data from the three testing sessions. Although the cohort as a whole demonstrated a graded response on several measures, there was high variability across subjects, with subsets exhibiting graded, threshold, or minimal responses. Some subjects experienced greater variability in their CDS performance across the three days than the change induced by reducing stimulation. For several tasks, a subset of subjects exhibited improved performance at one or more of the reduced conditions. Reducing stimulation did not affect all subjects equally, nor did it uniformly affect each subject's performance across tasks. These results indicate that altered recruitment of neural structures can differentially affect motor capabilities and demonstrate the need for clinical consideration of the effects on multiple symptoms across several days when selecting DBS parameters.
ContributorsConovaloff, Alison (Author) / Abbas, James (Thesis advisor) / Krishnamurthi, Narayanan (Committee member) / Mahant, Padma (Committee member) / Jung, Ranu (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Advances in implantable MEMS technology has made possible adaptive micro-robotic implants that can track and record from single neurons in the brain. Development of autonomous neural interfaces opens up exciting possibilities of micro-robots performing standard electrophysiological techniques that would previously take researchers several hundred hours to train and achieve the desired skill level. It would result in more reliable and adaptive neural interfaces that could record optimal neural activity 24/7 with high fidelity signals, high yield and increased throughput. The main contribution here is validating adaptive strategies to overcome challenges in autonomous navigation of microelectrodes inside the brain. The following issues pose significant challenges as brain tissue is both functionally and structurally dynamic: a) time varying mechanical properties of the brain tissue-microelectrode interface due to the hyperelastic, viscoelastic nature of brain tissue b) non-stationarities in the neural signal caused by mechanical and physiological events in the interface and c) the lack of visual feedback of microelectrode position in brain tissue. A closed loop control algorithm is proposed here for autonomous navigation of microelectrodes in brain tissue while optimizing the signal-to-noise ratio of multi-unit neural recordings. The algorithm incorporates a quantitative understanding of constitutive mechanical properties of soft viscoelastic tissue like the brain and is guided by models that predict stresses developed in brain tissue during movement of the microelectrode. An optimal movement strategy is developed that achieves precise positioning of microelectrodes in the brain by minimizing the stresses developed in the surrounding tissue during navigation and maximizing the speed of movement. Results of testing the closed-loop control paradigm in short-term rodent experiments validated that it was possible to achieve a consistently high quality SNR throughout the duration of the experiment. At the systems level, new generation of MEMS actuators for movable microelectrode array are characterized and the MEMS device operation parameters are optimized for improved performance and reliability. Further, recommendations for packaging to minimize the form factor of the implant; design of device mounting and implantation techniques of MEMS microelectrode array to enhance the longevity of the implant are also included in a top-down approach to achieve a reliable brain interface.
ContributorsAnand, Sindhu (Author) / Muthuswamy, Jitendran (Thesis advisor) / Tillery, Stephen H (Committee member) / Buneo, Christopher (Committee member) / Abbas, James (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2013
Description
Spinal cord injury (SCI) disrupts the communication between supraspinal circuits and spinal circuits distal to the injury. This disruption causes changes in the motor abilities of the affected individual, but it can also be used as an opportunity to study motor control in the absence or limited presence of control from the brain. In the case of incomplete paraplegia, locomotion is impaired and often results in increased incidence of foot drag and decreased postural stability after injury. The overall goal of this work is to understand how changes in kinematics of movement and neural control of muscles effect locomotor coordination following SCI. Toward this end, we examined musculoskeletal parameters and kinematics of gait in rats with and without incomplete SCI (iSCI) and used an empirically developed computational model to test related hypotheses. The first study tested the hypothesis that iSCI causes a decrease in locomotor and joint angle movement complexity. A rat model was used to measure musculoskeletal properties and gait kinematics following mild iSCI. The data indicated joint-specific changes in kinematics in the absence of measurable muscle atrophy, particularly at the ankle as a result of the injury. Kinematic changes manifested as a decrease in complexity of ankle motion as indicated by measures of permutation entropy. In the second study, a new 2-dimensional computational model of the rat ankle combining forward and inverse dynamics was developed using the previously collected data. This model was used to test the hypothesis that altered coordination of flexor and extensor muscles (specifically alteration in burst shape and timing) acting at the ankle joint could be responsible for increases in incidence of foot drag following injury. Simulation results suggest a time course for changes in neural control following injury that begins with foot drag and decreased delay between antagonistic muscle activations. Following this, beneficial adaptations in muscle activation profile and ankle kinematics counteract the decreased delay to allow foot swing. In both studies, small changes in neural control caused large changes in behavior, particularly at the ankle. Future work will further examine the role of neural control of hindlimb in rat locomotion following iSCI.
ContributorsHillen, Brian (Author) / Jung, Ranu (Thesis advisor) / Abbas, James (Committee member) / Muthuswamy, Jit (Committee member) / Jindrich, Devin (Committee member) / Yamaguchi, Gary (Committee member) / Arizona State University (Publisher)
Created2012
Description
Humans moving in the environment must frequently change walking speed and direction to negotiate obstacles and maintain balance. Maneuverability and stability requirements account for a significant part of daily life. While constant-average-velocity (CAV) human locomotion in walking and running has been studied extensively unsteady locomotion has received far less attention. Although some studies have described the biomechanics and neurophysiology of maneuvers, the underlying mechanisms that humans employ to control unsteady running are still not clear. My dissertation research investigated some of the biomechanical and behavioral strategies used for stable unsteady locomotion. First, I studied the behavioral level control of human sagittal plane running. I tested whether humans could control running using strategies consistent with simple and independent control laws that have been successfully used to control monopod robots. I found that humans use strategies that are consistent with the distributed feedback control strategies used by bouncing robots. Humans changed leg force rather than stance duration to control center of mass (COM) height. Humans adjusted foot placement relative to a "neutral point" to change running speed increment between consecutive flight phases, i.e. a "pogo-stick" rather than a "unicycle" strategy was adopted to change running speed. Body pitch angle was correlated by hip moments if a proportional-derivative relationship with time lags corresponding to pre-programmed reaction (87 ± 19 ms) was assumed. To better understand the mechanisms of performing successful maneuvers, I studied the functions of joints in the lower extremities to control COM speed and height. I found that during stance, the hip functioned as a power generator to change speed. The ankle switched between roles as a damper and torsional spring to contributing both to speed and elevation changes. The knee facilitated both speed and elevation control by absorbing mechanical energy, although its contribution was less than hip or ankle. Finally, I studied human turning in the horizontal plane. I used a morphological perturbation (increased body rotational inertia) to elicit compensational strategies used to control sidestep cutting turns. Humans use changes to initial body angular speed and body pre-rotation to prevent changes in braking forces.
ContributorsQiao, Mu, 1981- (Author) / Jindrich, Devin L (Thesis advisor) / Dounskaia, Natalia (Committee member) / Abbas, James (Committee member) / Hinrichs, Richard (Committee member) / Santello, Marco (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
Description
Injuries and death associated with fall incidences pose a significant burden to society, both in terms of human suffering and economic losses. The main aim of this dissertation is to study approaches that can reduce the risk of falls. One major subset of falls is falls due to neurodegenerative disorders such as Parkinson’s disease (PD). Freezing of gait (FOG) is a major cause of falls in this population. Therefore, a new FOG detection method using wavelet transform technique employing optimal sampling window size, update time, and sensor placements for identification of FOG events is created and validated in this dissertation. Another approach to reduce the risk of falls in PD patients is to correctly diagnose PD motor subtypes. PD can be further divided into two subtypes based on clinical features: tremor dominant (TD), and postural instability and gait difficulty (PIGD). PIGD subtype can place PD patients at a higher risk for falls compared to TD patients and, they have worse postural control in comparison to TD patients. Accordingly, correctly diagnosing subtypes can help caregivers to initiate early amenable interventions to reduce the risk of falls in PIGD patients. As such, a method using the standing center-of-pressure time series data has been developed to identify PD motor subtypes in this dissertation. Finally, an intervention method to improve dynamic stability was tested and validated. Unexpected perturbation-based training (PBT) is an intervention method which has shown promising results in regard to improving balance and reducing falls. Although PBT has shown promising results, the efficacy of such interventions is not well understood and evaluated. In other words, there is paucity of data revealing the effects of PBT on improving dynamic stability of walking and flexible gait adaptability. Therefore, the effects
of three types of perturbation methods on improving dynamics stability was assessed. Treadmill delivered translational perturbations training improved dynamic stability, and adaptability of locomotor system in resisting perturbations while walking.
of three types of perturbation methods on improving dynamics stability was assessed. Treadmill delivered translational perturbations training improved dynamic stability, and adaptability of locomotor system in resisting perturbations while walking.
ContributorsRezvanian, Saba (Author) / Lockhart, Thurmon (Thesis advisor) / Buneo, Christopher (Committee member) / Lieberman, Abraham (Committee member) / Abbas, James (Committee member) / Deep, Aman (Committee member) / Arizona State University (Publisher)
Created2019
Description
Intracellular voltage recordings from single neurons in vitro and in vivo have been fundamental to our understanding of neuronal function. Conventional electrodes and associated positioning systems for intracellular recording in vivo are large and bulky, which has largely restricted their use to single-channel recording from anesthetized animals. Further, intracellular recordings are very cumbersome, requiring a high degree of skill not readily achieved in a typical laboratory. This dissertation presents a robotic, head-mountable, MEMS (Micro-Electro-Mechanical Systems) based intracellular recording system to overcome the above limitations associated with form-factor, scalability and highly skilled and tedious manual operations required for intracellular recordings. This system combines three distinct technologies: 1) novel microscale, polycrystalline silicon-based electrode for intracellular recording, 2) electrothermal microactuators for precise microscale navigation of the electrode and 3) closed-loop control algorithm for autonomous movement and positioning of electrode inside single neurons. First, two distinct designs of polysilicon-based microscale electrodes were fabricated and tested for intracellular recordings. In the first approach, tips of polysilicon microelectrodes were milled to nanoscale dimensions (<300 nm) using focused ion beam (FIB) to develop polysilicon nanoelectrodes. Polysilicon nanoelectrodes recorded >1.5 mV amplitude, positive-going action potentials and synaptic potentials from neurons in the abdominal ganglion of Aplysia Californica. In the second approach, polysilicon microelectrodes were integrated with miniaturized glass micropipettes filled with electrolyte to fabricate glass-polysilicon microelectrodes. These electrodes consistently recorded high fidelity intracellular potentials from neurons in the abdominal ganglion of Aplysia Californica (Resting Potentials < -35 mV, Action Potentials > 60 mV) as well as the rat motor cortex (Resting Potentials < -50 mV). Next, glass-polysilicon microelectrodes were coupled with microscale electrothermal actuators and controller for autonomous intracellular recordings from single neurons in the abdominal ganglion. Consistent resting potentials (< -35 mV) and action potentials (> 60 mV) were recorded after each successful penetration attempt with the controller and microactuated glass-polysilicon microelectrodes. The success rate of penetration and quality of recordings achieved using electrothermal microactuators were comparable to that of conventional positioning systems. Finally, the feasibility of this miniaturized system to obtain intracellular recordings from single neurons in the motor cortex of rats in vivo is also demonstrated. The MEMS-based system offers significant advantages: 1) reduction in overall size for potential use in behaving animals, 2) scalable approach to potentially realize multi-channel recordings and 3) a viable method to fully automate measurement of intracellular recordings.
ContributorsSampath Kumar, Swathy (Author) / Muthuswamy, Jit (Thesis advisor) / Abbas, James (Committee member) / Hamm, Thomas (Committee member) / Christen, Jennifer Blain (Committee member) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2018
Description
Presented below is the design and fabrication of prosthetic components consisting of an attachment, tactile sensing, and actuator systems with Fused Filament Fabrication (FFF) technique. The attachment system is a thermoplastic osseointegrated upper limb prosthesis for average adult trans-humeral amputation with mechanical properties greater than upper limb skeletal bone. The prosthetic designed has: a one-step surgical process, large cavities for bone tissue ingrowth, uses a material that has an elastic modulus less than skeletal bone, and can be fabricated on one system.
FFF osseointegration screw is an improvement upon the current two-part osseointegrated prosthetics that are composed of a fixture and abutment. The current prosthetic design requires two invasive surgeries for implantation and are made of titanium, which has an elastic modulus greater than bone. An elastic modulus greater than bone causes stress shielding and overtime can cause loosening of the prosthetic.
The tactile sensor is a thermoplastic piezo-resistive sensor for daily activities for a prosthetic’s feedback system. The tactile sensor is manufactured from a low elastic modulus composite comprising of a compressible thermoplastic elastomer and conductive carbon. Carbon is in graphite form and added in high filler ratios. The printed sensors were compared to sensors that were fabricated in a gravity mold to highlight the difference in FFF sensors to molded sensors. The 3D printed tactile sensor has a thickness and feel similar to human skin, has a simple fabrication technique, can detect forces needed for daily activities, and can be manufactured in to user specific geometries.
Lastly, a biomimicking skeletal muscle actuator for prosthetics was developed. The actuator developed is manufactured with Fuse Filament Fabrication using a shape memory polymer composite that has non-linear contractile and passive forces, contractile forces and strains comparable to mammalian skeletal muscle, reaction time under one second, low operating temperature, and has a low mass, volume, and material costs. The actuator improves upon current prosthetic actuators that provide rigid, linear force with high weight, cost, and noise.
FFF osseointegration screw is an improvement upon the current two-part osseointegrated prosthetics that are composed of a fixture and abutment. The current prosthetic design requires two invasive surgeries for implantation and are made of titanium, which has an elastic modulus greater than bone. An elastic modulus greater than bone causes stress shielding and overtime can cause loosening of the prosthetic.
The tactile sensor is a thermoplastic piezo-resistive sensor for daily activities for a prosthetic’s feedback system. The tactile sensor is manufactured from a low elastic modulus composite comprising of a compressible thermoplastic elastomer and conductive carbon. Carbon is in graphite form and added in high filler ratios. The printed sensors were compared to sensors that were fabricated in a gravity mold to highlight the difference in FFF sensors to molded sensors. The 3D printed tactile sensor has a thickness and feel similar to human skin, has a simple fabrication technique, can detect forces needed for daily activities, and can be manufactured in to user specific geometries.
Lastly, a biomimicking skeletal muscle actuator for prosthetics was developed. The actuator developed is manufactured with Fuse Filament Fabrication using a shape memory polymer composite that has non-linear contractile and passive forces, contractile forces and strains comparable to mammalian skeletal muscle, reaction time under one second, low operating temperature, and has a low mass, volume, and material costs. The actuator improves upon current prosthetic actuators that provide rigid, linear force with high weight, cost, and noise.
ContributorsLathers, Steven (Author) / La Belle, Jeffrey (Thesis advisor) / Vowels, David (Committee member) / Lockhart, Thurmon (Committee member) / Abbas, James (Committee member) / McDaniel, Troy (Committee member) / Arizona State University (Publisher)
Created2017
Description
Transcranial electrical stimulation (tES) is a non-invasive brain stimulation therapy that has shown potential in improving motor, physiological and cognitive functions in healthy and diseased population. Typical tES procedures involve application of weak current (< 2 mA) to the brain via a pair of large electrodes placed on the scalp. While the therapeutic benefits of tES are promising, the efficacy of tES treatments is limited by the knowledge of how current travels in the brain. It has been assumed that the current density and electric fields are the largest, and thus have the most effect, in brain structures nearby the electrodes. Recent studies using finite element modeling (FEM) have suggested that current patterns in the brain are diffuse and not concentrated in any particular brain structure. Although current flow modeling is useful means of informing tES target optimization, few studies have validated tES FEM models against experimental measurements. MREIT-CDI can be used to recover magnetic flux density caused by current flow in a conducting object. This dissertation reports the first comparisons between experimental data from in-vivo human MREIT-CDI during tES and results from tES FEM using head models derived from the same subjects. First, tES FEM pipelines were verified by confirming FEM predictions agreed with analytic results at the mesh sizes used and that a sufficiently large head extent was modeled to approximate results on human subjects. Second, models were used to predict magnetic flux density, and predicted and MREIT-CDI results were compared to validate and refine modeling outcomes. Finally, models were used to investigate inter-subject variability and biological side effects reported by tES subjects. The study demonstrated good agreements in patterns between magnetic flux distributions from experimental and simulation data. However, the discrepancy in scales between simulation and experimental data suggested that tissue conductivities typically used in tES FEM might be incorrect, and thus performing in-vivo conductivity measurements in humans is desirable. Overall, in-vivo MREIT-CDI in human heads has been established as a validation tool for tES predictions and to study the underlying mechanisms of tES therapies.
ContributorsIndahlastari, Aprinda (Author) / Sadleir, Rosalind J (Thesis advisor) / Abbas, James (Committee member) / Frakes, David (Committee member) / Kleim, Jeffrey (Committee member) / Kodibagkar, Vikram (Committee member) / Arizona State University (Publisher)
Created2017
Description
For two centuries, electrical stimulation has been the conventional method for interfacing with the nervous system. As interfaces with the peripheral nervous system become more refined and higher-resolution, several challenges appear, including immune responses to invasive electrode application, large-to-small axon recruitment order, and electrode size-dependent spatial selectivity. Optogenetics offers a solution that is less invasive, more tissue-selective, and has small-to-large axon recruitment order. By adding genes to express photosensitive proteins optogenetics provides neuroscientists the ability to genetically select cell populations to stimulate with simple illumination. However, optogenetic stimulation of peripheral nerves uses diffuse light to activate the photosensitive neural cell lines. To increase the specificity of stimulus response, research was conducted to test the hypothesis that multiple, focused light emissions placed around the circumference of optogenetic mouse sciatic nerve could be driven to produce differential responses in hindlimb motor movement depending on the pattern of light presented. A Monte Carlo computer simulation was created to model the number of emitters, the light emission size, and the focal power of accompanying micro-lenses to provide targeted stimulation to select regions within the sciatic nerve. The computer simulation results were used to parameterize the design of micro-lenses. By modeling multiple focused beams, only fascicles within a nerve diameter less than 1 mm are expected to be fully accessible to focused optical stimulation; a minimum of 4 light sources is required to generate a photon intensity at a point in a nerve over the initial contact along its surface. To elicit the same effect in larger nerves, focusing lenses would require a numerical aperture > 1. Microlenses which met the simulation requirements were fabricated and deployed on a flexible nerve cuff which was used to stimulate the sciatic nerve in optogenetic mice. Motor neuron responses from this stimulation were compared to global illumination; stimulation using the optical cuff resulted in fine motor movement of the extensor muscles of the digits in the hindlimb. Increasing optical power resulted in a shift to gross motor movement of hindlimb. Finally, varying illumination intensity across the cuff showed changes in the extension of individual digits.
ContributorsFritz, Nicholas (Author) / Blain Christen, Jennifer (Thesis advisor) / Abbas, James (Committee member) / Goryll, Michael (Committee member) / Sadleir, Rosalind (Committee member) / Helms-Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2021