Conference Papers

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Author: search.filters.author.Kamath, A.J.

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    A novel device to monitor mobilization of fingers during treatment for stiffness of tendons
    (2010) Gonda, J.M.; Kamath, A.J.; Venkatesh Prasad, H.N.; Jagannath Kamath, B.
    Conceptualization and development of a novel device to monitor mobilization of fingers of a patient suffering from post-traumatic stiffness of the tendons is presented in this paper. Effectiveness of the treatment depends largely on this component of recovery and is unfortunately beyond the scope of continuous vigil by the doctor. The major post-operative procedure is to keep flexing and extending the fingers, either independently or with external support, usually with the other hand. The patient has to do this diligently and hence monitoring this exercise is of concern. The proposed novel idea is a monitoring system which keeps track of the movements of the fingers using linear ratiometric Hall-effect sensors (Allegro-1321) and magnets attached to the fingers. This can provide reliable data to the doctor to ascertain whether the patient is actually doing his part in effecting a speedy recovery for himself, thus improving the overall efficacy of the treatment. ©2010 IEEE.
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    FRI Modelling of Fourier Descriptors
    (Institute of Electrical and Electronics Engineers Inc., 2019) Kamath, A.J.; Rudresh, S.; Seelamantula, C.S.
    Fourier descriptors are used to parametrically represent closed contours. In practice, a finite set of Fourier descriptors can model a large class of smooth contours. In this paper, we propose a method for estimating the Fourier descriptors of a given contour from its partial samples. We take a sampling-theoretic approach to model the x and y coordinate functions of the shape and express them as a sum of weighted complex exponentials, which belong to the class of finite-rate-of-innovation (FRI) signals. The weights represent the Fourier descriptors of the shape. We use the FRI framework to estimate the shape parameters reliably from noisy and partial measurements. We model non-uniformities in sampling using the sampling jitter model and employ a prefiltering process to reduce the effect of measurement noise and jitter. The average sampling interval is estimated by a block annihilating filter, which is then followed by the estimation of Fourier descriptors using least-squares fitting. We demonstrate the robustness of the proposed algorithm to noise and sampling jitter. Monte Carlo performance analysis shows that the variances of the estimators are close to the Cramér-Rao lower bounds. We present results for outlining shapes in synthetic as well as real images. © 2019 IEEE.