Power Independent EMG Based Gesture Recognition for Robotics

Li, Ling and Looney, D. and Park, C. and Rehman, N.U. and Mandic, Danilo P. (2011) Power Independent EMG Based Gesture Recognition for Robotics. In: Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE. (The full text of this publication is not available from this repository)

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Official URL
http://www.cs.kent.ac.uk/pubs/2011/3182

Abstract

A robot control system using four different gestures from an arm is presented. This is achieved based on surface Electromyograph (EMG) measurements of groups of arm muscles. The cross-information is preserved through a simultaneous processing of EMG channels using a recent multivariate extension of Empirical Mode Decomposition (EMD). Next, phase synchrony measures are employed to make the system robust to different power levels due to electrode placements and impedances. The multiple pairwise muscle synchronies are used as features of a discrete gesture space comprising four gestures (flexion, extension, pronation, supination). Simulations on real-time robot control illustrate the enhanced accuracy and robustness of the proposed methodology.

Item Type: Conference or workshop item (UNSPECIFIED)
Uncontrolled keywords: determinacy analysis, Craig interpolants
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Computational Intelligence Group
Faculties > Science Technology and Medical Studies > School of Computing > Future Computing Group
Depositing User: Caroline Li
Date Deposited: 21 Sep 2012 09:49
Last Modified: 14 Jul 2014 10:51
Resource URI: http://kar.kent.ac.uk/id/eprint/30734 (The current URI for this page, for reference purposes)
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