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- Creators: Brahms, Johannes, 1833-1897
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
Multiple Sclerosis, an autoimmune disease, is one of the most common neurological disorder in which demyelinating of the axon occurs. The main symptoms of MS disease are fatigue, vision problems, stability issue, balance problems. Unfortunately, currently available treatments for this disease do not always guarantee the improvement of the condition of the MS patient and there has not been an accurate mechanism to measure the effectiveness of the treatment due to inter-patient heterogeneity. The factors that count for varying the performance of MS patients include environmental setting, weather, psychological status, dressing style and more. Also, patients may react differently while examined at specially arranged setting and this may not be the same while he/she is at home. Hence, it becomes a major problem for MS patients that how effectively a treatment slows down the progress of the disease and gives a relief for the patient. This thesis is trying to build a reliable system to estimate how good a treatment is for MS patients. Here I study the kinematic variables such as velocity of walking, stride length, variability and so on to find and compare the variations of the patient after a treatment given by the doctor, and trace these parameters for some patients after the treatment effect subdued.
ContributorsYin, Siyang (Author) / He, Jiping (Thesis advisor) / Pizziconi, Vincent (Committee member) / Towe, Bruce (Committee member) / Arizona State University (Publisher)
Created2012
ContributorsBrahms, Johannes, 1833-1897 (Composer)
ContributorsBrahms, Johannes, 1833-1897 (Composer)
ContributorsBrahms, Johannes, 1833-1897 (Composer)
ContributorsBrahms, Johannes, 1833-1897 (Composer)
ContributorsBrahms, Johannes, 1833-1897 (Composer)
Description
Virtual environments are used for many physical rehabilitation and therapy purposes with varying degrees of success. An important feature for a therapy environment is the real-time monitoring of a participants' movement performance. Such monitoring can be used to evaluate the environment in addition to the participant's learning. Methods for monitoring and evaluation include tracking kinematic performance as well as monitoring muscle and brain activities through EMG and EEG technology. This study aims to observe trends in individual participants' motor learning based on changes in kinematic parameters and use those parameters to characterize different types of learners. This information can then guide EEG/EMG data analysis in the future. The evaluation of motor learning using kinematic parameters of performance typically compares averages of pre- and post-data to identify patterns of changes of various parameters. A key issue with using pre- and post-data is that individual participants perform differently and have different time-courses of learning. Furthermore, different parameters can evolve at independent rates. Finally, there is great variability in the movements at early stages of learning a task. To address these issues, a combined approach is proposed using robust regression, piece-wise regression and correlation to categorize different participant's motor learning. Using the mixed reality rehabilitation system developed at Arizona State University, it was possible to engage participants in motor learning, as revealed by improvements in kinematic parameters. A combination of robust regression, piecewise regression and correlation were used to reveal trends and characterize participants based on motor learning of three kinematic parameters: trajectory error, supination error and the number of phases in the velocity profile.
ContributorsAttygalle, Suneth Satoshi (Author) / He, Jiping (Thesis advisor) / Rikakais, Thanassis (Committee member) / Iasemidis, Leonidas (Committee member) / Arizona State University (Publisher)
Created2010
ContributorsBrahms, Johannes, 1833-1897 (Composer)