Matching Items (35)
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- All Subjects: Neurosciences
- Creators: Santello, Marco
- Status: Published
Description
Stroke occurs when the blood supply to part of the brain is interrupted or reduced, preventing brain tissue from getting oxygen and nutrients, thus causing brain cells to die. Stroke is the 5th leading cause of death in the United States and is one of the major causes of disability. Conventional therapy is a form of stroke rehabilitation generally consisting of physical and occupational therapy. It focuses on customized exercises based on the patient’s feedback. Physical therapy includes exercises such as weight bearing (affected arm), vibration of affected muscle and gravity-eliminated movement of affected arm. Overall physical therapy aims at strengthening muscle groups and aides in the relearning process. Occupational aspect of conventional therapy includes activities of daily living (ADL) such as dressing, self-feeding, grooming and toileting. Overall occupational therapy focuses on improving the daily activities performed by individuals. In comparison to conventional therapy, robotic therapy is relatively newer therapy. It uses robotic devices to perform repetitive motions and delivers high dosage and high intensity training to stroke patients. Based on the research studies reviewed, it is known that neuroplasticity in stroke patients is linked to interventions which are high in dosage, intensity, repetition, difficulty, salience. Peer-reviewed literature suggests robotic therapy might be a viable option for recovery in stroke patients. However, the extent to which robotic therapy may provide greater benefits than conventional therapy remains unclear. This thesis addresses the key components of a study design for comparing the efficacy of robotic therapy relative to conventional therapy to improve upper limb sensorimotor function in stroke survivors. The study design is based on an extensive review of the literature of stroke clinical trials and robotic therapy studies, analyses of the capabilities of a robotic therapy device (M2, Fourier Intelligence), and pilot data collected on healthy controls to create a pipeline of tasks and analyses to extract biomarkers of sensorimotor functional changes. This work has laid the foundation for a pilot longitudinal study that will be conducted at the Barrow Neurological Institute, Phoenix, AZ, where conventional and robotic therapy will be compared in a small cohort of stroke survivors.
ContributorsThomas, Lovein (Author) / Santello, Marco (Thesis advisor) / Kleim, Jeffrey (Committee member) / Maruyama, Trent (Committee member) / Arizona State University (Publisher)
Created2021
Description
In recent years, brain signals have gained attention as a potential trait for biometric-based security systems and laboratory systems have been designed. A real-world brain-based security system requires to be usable, accurate, and robust. While there have been developments in these aspects, there are still challenges to be met. With regard to usability, users need to provide lengthy amount of data compared to other traits such as fingerprint and face to get authenticated. Furthermore, in the majority of works, medical sensors are used which are more accurate compared to commercial ones but have a tedious setup process and are not mobile. Performance wise, the current state-of-art can provide acceptable accuracy on a small pool of users data collected in few sessions close to each other but still falls behind on a large pool of subjects over a longer time period. Finally, a brain security system should be robust against presentation attacks to prevent adversaries from gaining access to the system.
This dissertation proposes E-BIAS (EEG-based Identification and Authentication System), a brain-mobile security system that makes contributions in three directions. First, it provides high performance on signals with shorter lengths collected by commercial sensors and processed with lightweight models to meet the computation/energy capacity of mobile devices. Second, to evaluate the system's robustness a novel presentation attack was designed which challenged the literature's presumption of intrinsic liveness property for brain signals. Third, to bridge the gap, I formulated and studied the brain liveness problem and proposed two solution approaches (model-aware & model agnostic) to ensure liveness and enhance robustness against presentation attacks. Under each of the two solution approaches, several methods were suggested and evaluated against both synthetic and manipulative classes of attacks (a total of 43 different attack vectors). Methods in both model-aware and model-agnostic approaches were successful in achieving an error rate of zero (0%). More importantly, such error rates were reached in face of unseen attacks which provides evidence of the generalization potentials of the proposed solution approaches and methods. I suggested an adversarial workflow to facilitate attack and defense cycles to allow for enhanced generalization capacity for domains in which the decision-making process is non-deterministic such as cyber-physical systems (e.g. biometric/medical monitoring, autonomous machines, etc.). I utilized this workflow for the brain liveness problem and was able to iteratively improve the performance of both the designed attacks and the proposed liveness detection methods.
ContributorsSohankar Esfahani, Mohammad Javad (Author) / Gupta, Sandeep K.S. (Thesis advisor) / Santello, Marco (Committee member) / Dasgupta, Partha (Committee member) / Banerjee, Ayan (Committee member) / Arizona State University (Publisher)
Created2021
Description
Locomotion in natural environments requires coordinated movements from multiple body parts, and precise adaptations when changes in the environment occur. The contributions of the neurons of the motor cortex underlying these behaviors are poorly understood, and especially little is known about how such contributions may differ based on the anatomical and physiological characteristics of neurons. To elucidate the contributions of motor cortical subpopulations to movements, the activity of motor cortical neurons, muscle activity, and kinematics were studied in the cat during a variety of locomotion tasks requiring accurate foot placement, including some tasks involving both expected and unexpected perturbations of the movement environment. The roles of neurons with two types of neuronal characteristics were studied: the existence of somatosensory receptive fields located at the shoulder, elbow, or wrist of the contralateral forelimb; and the existence projections through the pyramidal tract, including fast- and slow-conducting subtypes.
Distinct neuronal adaptations between simple and complex locomotion tasks were observed for neurons with different receptive field properties and fast- and slow-conducting pyramidal tract neurons. Feedforward and feedback-driven kinematic control strategies were observed for adaptations to expected and unexpected perturbations, respectively, during complex locomotion tasks. These kinematic differences were reflected in the response characteristics of motor cortical neurons receptive to somatosensory information from different parts of the forelimb, elucidating roles for the various neuronal populations in accommodating disturbances in the environment during behaviors. The results show that anatomical and physiological characteristics of motor cortical neurons are important for determining if and how neurons are involved in precise control of locomotion during natural behaviors.
Distinct neuronal adaptations between simple and complex locomotion tasks were observed for neurons with different receptive field properties and fast- and slow-conducting pyramidal tract neurons. Feedforward and feedback-driven kinematic control strategies were observed for adaptations to expected and unexpected perturbations, respectively, during complex locomotion tasks. These kinematic differences were reflected in the response characteristics of motor cortical neurons receptive to somatosensory information from different parts of the forelimb, elucidating roles for the various neuronal populations in accommodating disturbances in the environment during behaviors. The results show that anatomical and physiological characteristics of motor cortical neurons are important for determining if and how neurons are involved in precise control of locomotion during natural behaviors.
ContributorsStout, Eric (Author) / Beloozerova, Irina N (Thesis advisor) / Dounskaia, Natalia (Thesis advisor) / Buneo, Christopher A (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2015
Description
Our ability to estimate the position of our body parts in space, a fundamentally proprioceptive process, is crucial for interacting with the environment and movement control. For proprioception to support these actions, the Central Nervous System has to rely on a stored internal representation of the body parts in space. However, relatively little is known about this internal representation of arm position. To this end, I developed a method to map proprioceptive estimates of hand location across a 2-d workspace. In this task, I moved each subject's hand to a target location while the subject's eyes were closed. After returning the hand, subjects opened their eyes to verbally report the location of where their fingertip had been. Then, I reconstructed and analyzed the spatial structure of the pattern of estimation errors. In the first couple of experiments I probed the structure and stability of the pattern of errors by manipulating the hand used and tactile feedback provided when the hand was at each target location. I found that the resulting pattern of errors was systematically stable across conditions for each subject, subject-specific, and not uniform across the workspace. These findings suggest that the observed structure of pattern of errors has been constructed through experience, which has resulted in a systematically stable internal representation of arm location. Moreover, this representation is continuously being calibrated across the workspace. In the next two experiments, I aimed to probe the calibration of this structure. To this end, I used two different perturbation paradigms: 1) a virtual reality visuomotor adaptation to induce a local perturbation, 2) and a standard prism adaptation paradigm to induce a global perturbation. I found that the magnitude of the errors significantly increased to a similar extent after each perturbation. This small effect indicates that proprioception is recalibrated to a similar extent regardless of how the perturbation is introduced, suggesting that sensory and motor changes may be two independent processes arising from the perturbation. Moreover, I propose that the internal representation of arm location might be constructed with a global solution and not capable of local changes.
ContributorsRincon Gonzalez, Liliana (Author) / Helms Tillery, Stephen I (Thesis advisor) / Buneo, Christopher A (Thesis advisor) / Santello, Marco (Committee member) / Santos, Veronica (Committee member) / Kleim, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2012
Description
Although previous studies have elucidated the role of position feedback in the regulation of movement, the specific contribution of Golgi tendon organs (GTO) in force feedback, especially in stabilizing voluntary limb movements, has remained theoretical due to limitations in experimental techniques. This study aims to establish force feedback regulation mediated by GTO afferent signals in two phases. The first phase of this study consisted of simulations using a neuromusculoskeletal model of the monoarticular elbow flexor (MEF) muscle group, assess the impact of force feedback in maintaining steady state interaction forces against variable environmental stiffness. Three models were trained to accurately reach an interaction force of 40N, 50N and 60N respectively, using a fixed stiffness level. Next, the environment stiffness was switched between untrained levels for open loop (OL) and closed loop (CL) variants of the same model. Results showed that compared to OL, CL showed decreased force deviations by 10.43%, 12.11% and 13.02% for each of the models. Most importantly, it is also observed that in the absence of force feedback, environment stiffness is found to have an effect on the interaction force. In the second phase, human subjects were engaged in experiments utilizing an instrumented elbow exoskeleton that applied loads to the MEF muscle group, closely mimicking the simulation conditions. The experiments consisted of reference, blind and catch trial types, and 3 stiffness levels. Subjects were first trained to reach for a predetermined target force. During catch trials, stiffness levels were randomized between reaches. Responses obtained from these experiments showed that subjects were able to regulate forces with no significant effects of trial type or stiffness level. Since experimental results align closely with that of closed loop model simulations, the presence of force feedback mechanisms mediated by GTO within the human neuromuscular system is established. This study not only unveils the critical involvement of GTO in force feedback but also emphasizes the importance of understanding these mechanisms for developing advanced neuroprosthetics and rehabilitation strategies, shedding light on the intricate interplay between sensory inputs and motor responses in human proprioception.
ContributorsAbishek, Kevin (Author) / Lee, Hyunglae (Thesis advisor) / Buneo, Christopher (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2023