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Power Independent EMG Based Gesture Recognition for Robotics

Li, Ling and Looney, David and Park, Cheolsoo and Rehman, Naveed U. and Mandic, Danilo P. (2011) Power Independent EMG Based Gesture Recognition for Robotics. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, pp. 182-196. ISBN 978-1-4244-4121-1. E-ISBN 978-1-4577-1589-1. (doi:10.1109/IEMBS.2011.6090036) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1109/IEMBS.2011.6090036

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: Book section
DOI/Identification number: 10.1109/IEMBS.2011.6090036
Uncontrolled keywords: biomedical electrodes; biomedical measurement; electromyography; gesture recognition; medical robotics; medical signal processing; real-time systems
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Faculties > Sciences > School of Computing > Computational Intelligence Group
Faculties > Sciences > School of Computing > Data Science
Depositing User: Caroline Li
Date Deposited: 21 Sep 2012 09:49 UTC
Last Modified: 07 Feb 2020 04:04 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/30734 (The current URI for this page, for reference purposes)
Li, Ling: https://orcid.org/0000-0002-4026-0216
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