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Showing papers by "Shyamanta M. Hazarika published in 2009"


Proceedings ArticleDOI
30 Oct 2009
TL;DR: In a study involving six subjects, the methodology to classify grasp types based on two channel forearm electromyogram signals achieved an average recognition rate of 86%; better than that reported in the liteature.
Abstract: In this paper, we present a methodology to classify grasp types based on two channel forearm electromyogram signals. Six grasp types are identified. Classification is through support vector machine using radial basis function kernel based on sum of wavelet decomposition coefficients of the electromyogram signals. In a study involving six subjects, we achieved an average recognition rate of 86%; better than that reported in the liteature.

7 citations


Book ChapterDOI
01 Jan 2009

1 citations


Book ChapterDOI
01 Jan 2009

1 citations