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Sample Entropy Based Selection of Wavelet Decomposition Level for Finger Movement Recognition Using EMG

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Progress in Advanced Computing and Intelligent Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 713))

Abstract

This paper reports the recognition of five fingermovements using forearm EMG signals. A relationship between the sample entropy (SampEn) of EMG signals at four wavelet decomposition levels and classification accuracy has been established. Experiments with the EMG at third level of wavelet decomposition can classify the finger movements with a maximum accuracy of 95.5%. These results show that EMG at the decomposition level which possess minimum SampEn produces the maximum classification accuracy. The experimental result shows that this relationship is a very useful criterion for selection of wavelet decomposition level to recognize EMG-based finger movements.

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Acknowledgements

Centre of Excellence in Machine Learning and Big Data Analysis, Tezpur University, funded by Ministry of HRD, Government of India.

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Authors and Affiliations

  1. Embedded Systems and Robotics Laboratory, Tezpur University, Tezpur, 784028, India

    Nabasmita Phukan & Nayan M. Kakoty

Authors
  1. Nabasmita Phukan
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  2. Nayan M. Kakoty
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Correspondence to Nayan M. Kakoty .

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Editors and Affiliations

  1. Department of Computer Science, Rama Devi Women's University, Bhubaneswar, Odisha, India

    Bibudhendu Pati

  2. Department of Computer Science, Rama Devi Women's University, Bhubaneswar, Odisha, India

    Chhabi Rani Panigrahi

  3. Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India

    Sudip Misra

  4. Department of Computer Science, Central University of Rajasthan, Jaipur, Rajasthan, India

    Arun K. Pujari

  5. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Rourkela, Odisha, India

    Sambit Bakshi

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Phukan, N., Kakoty, N.M. (2019). Sample Entropy Based Selection of Wavelet Decomposition Level for Finger Movement Recognition Using EMG. In: Pati, B., Panigrahi, C., Misra, S., Pujari, A., Bakshi, S. (eds) Progress in Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 713. Springer, Singapore. https://doi.org/10.1007/978-981-13-1708-8_6

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  • DOI: https://doi.org/10.1007/978-981-13-1708-8_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1707-1

  • Online ISBN: 978-981-13-1708-8

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