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  • Techniques of EMG signal analysis: detection, processing, classification and applications

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    72245_1.pdf (700.7Kb)
    Author(s)
    Reaz, MBI
    Hussain, MS
    Mohd-Yasin, F
    Griffith University Author(s)
    Mohd-Yasin, Faisal
    Year published
    2006
    Metadata
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    Abstract
    Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human ...
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    Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications.
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    Journal Title
    Biological Procedures Online
    Volume
    8
    Issue
    1
    DOI
    https://doi.org/10.1251/bpo115
    Copyright Statement
    © 2006 Reaz et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Subject
    Biomedical engineering not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/46708
    Collection
    • Journal articles

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