Browsing by Author "Celik, Ozkan"

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    Evaluation of Velocity Estimation Methods Based on Their Effect on Haptic Device Performance
    (IEEE, 2018) Chawda, Vinay; Celik, Ozkan; O’Malley, Marcia K.
    This paper comparatively evaluates the effect of real-time velocity estimation methods on the passivity and fidelity of virtual walls implemented using haptic interfaces. Impedance width or Z-width is a fundamental measure of performance in haptic devices. Limited accuracy of velocity estimates from position encoder data is an impediment in improving the Z-width in haptic interfaces. We study the efficacy of Levant's differentiator as a velocity estimator to allow passive implementation of higher stiffness virtual walls as compared to some of the commonly used velocity estimators in the field of haptics. We first experimentally demonstrate feasibility of Levant's differentiator as a velocity estimator for haptics applications by comparing Z-width performance achieved with Levant's differentiator and commonly used finite difference method (FDM) cascaded with a low-pass filter. A novel Z-width plotting technique combining the passivity and fidelity of haptic rendering is proposed, and used to compare the haptic device performance obtained with Levant's differentiator, FDM+low-pass filter, first-order adaptive windowing (FOAW), and Kalman-filter-based velocity estimation methods. Simulations and experiments conducted on a custom single degree-of-freedom haptic device demonstrate that the stiffest virtual walls are rendered with velocity estimated using Levant's differentiator, and the highest wall rendering fidelity is achieved by FOAW-based velocity estimation scheme.
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    Method and device for real-time differentiation of analog and digital signals
    (2018-03-06) Celik, Ozkan; Chawda, Vinay; O'malley, Marcia K.; Rice University; United States Patent and Trademark Office
    The controller includes a differentiating engine configured to receive an input signal value (ISV), wherein the ISV corresponds to state information for one selected from a group consisting of a controlled process and a user interface. The differentiating engine is further configured to determine an error between the ISV and an estimated input signal (EIS), estimate a frequency of the IS, select a plurality of pre-determined gains using the frequency, wherein at least one plurality of pre-determined gains is a suction control gain, determine a first estimated derivative of the input signal (EDIS) using the plurality of pre-determined gains and the error, and to output the first EDIS.
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    Neuromuscular Mechanisms of Movement Variability: Implications for Rehabilitation and Augmentation
    (2011) Celik, Ozkan; O'Malley, Marcia K.
    Although speed-accuracy trade-offs and planning and execution of rapid goaldirected movements have garnered significant research interest, far fewer studies have reported results on the lower end of the movement speed spectrum. Not only do very interesting observations exist that are unique to slow movements, but an explanation of these observations is highly relevant to motor function recovery and motor skill learning, where movements are typically slow at the initiation of therapy or learning, and movement speed increases through practice, exercise or therapy. In the first part of this thesis, based on data from nine stroke patients who underwent a month-long hybrid traditional and robotic therapy protocol, a correlation analysis shows that measures of movement quality based on minimum jerk theory for movement planning correlates significantly and strongly with clinical measures of motor impairment. In contrast, measures of movement speed lack statistical significance and show only weak to moderate correlations with clinical measures. These results constitute an important step towards establishing a much-needed bridge between clinical and robotic rehabilitation research communities. In the second part, the origins of movement intermittency or variability in slow movements are explored. A study with five healthy subjects who completed a manual circular tracking task shows that movement intermittency increases in distal direction along the arm during multi-joint movements. This result suggests that a neuromuscular noise option is favored against a submovement-based central planning alternative, as the source of variability in slow movements. An additional experimental study with eight healthy subjects who completed slow elbow flexion movements at a constant slow speed target under varying resistive torque levels demonstrates that resistive torques can significantly decrease movement speed variability. The relationship between resistive torque levels and speed variability, however, is not monotonic. This finding may constitute a basis for proper design of novel human skill augmentation methods for delicate tasks and improve motor rehabilitation and learning protocols. Finally, a neuro-musculoskeletal model of the elbow suggests that movement speed variability in slow movements cannot be solely attributed to variability in the mechanics of muscle force generation. Together, these analyses, simulations, and experiments shed light on variability in slow movements, and will inform the development of novel paradigms for robotic rehabilitation, motor skill learning and augmentation.