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EMG Pattern Recognition: A Systematic Review

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Information Systems and Management Science (ISMS 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 521))

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Abstract

EMG (electromyography), which records the electrical activity of our muscles, is a common test for muscle movement. This test helps determine whether there is a nerve injury or a muscle disease present, allowing the best course of treatment to be determined. EMG (electrical muscle activity) signals are used in a wide range of biomedical and neurological applications. It’s a quick overview of pattern recognition using EMG signals, explaining the various models and techniques available. EMG signals can be collected using needle electrodes or wearable devices like the Myo Armband for hand gesture recognition. For the purposes of this study, both cases were considered and analyzed. The electromyographic sensors found in the Myo armband can be used to create cost-effective and easy-to-use prototype models for a variety of applications. Traditional algorithms are characterized by complex computational methods and a high level of variability. Electromyographic signals, on the other hand, can now be analyzed thanks to advances in digital signal processing and mathematical models.

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Author information

Authors and Affiliations

  1. PAHER University, Udaipur, Rajasthan, India

    Sushama Dhumal

  2. CSE, Pacific University, Udaipur, Rajasthan, India

    Prashant Sharma

Authors
  1. Sushama Dhumal
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  2. Prashant Sharma
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Corresponding author

Correspondence to Sushama Dhumal .

Editor information

Editors and Affiliations

  1. Department of Computer Information Systems, University of Malta, Msida, Malta

    Lalit Garg

  2. Computer Science and Engineering, National Institute of Technology, Chhatisgarh, India

    Dilip Singh Sisodia

  3. Central University of Rajasthan, Ajmer, Rajasthan, India

    Nishtha Kesswani

  4. Computer Information Systems Department, University of Malta, Msida, Malta

    Joseph G Vella

  5. EMLYON Business School, Écully, France

    Imene Brigui

  6. Faculty of Information and Communication Technology, University of Malta, Msida, Malta

    Peter Xuereb

  7. Department of Computer Science and Communication, Ostfold University, Halden, Norway

    Sanjay Misra

  8. Computer Science and Engineering, National Institute of Technology, Chhattisgarh, India

    Deepak Singh

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Dhumal, S., Sharma, P. (2023). EMG Pattern Recognition: A Systematic Review. In: Garg, L., et al. Information Systems and Management Science. ISMS 2021. Lecture Notes in Networks and Systems, vol 521. Springer, Cham. https://doi.org/10.1007/978-3-031-13150-9_10

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