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Surface EMG Signal Classification Using Ensemble Algorithm, PCA and DWT for Robot Control

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Advanced Informatics for Computing Research (ICAICR 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 955))

Abstract

This paper presents a framework of surface electromyography signals based robotic arm prototype control using discrete wavelet transform, principle component analysis, ensemble algorithms and Arduino Uno controller. In this context, the sequential floating forward selection algorithm is used for sorting out the features based on their relevance. The performance of different ensemble algorithms is evaluated with various parameters like classification accuracy, sensitivity, specificity, false descriptive rate, positive predictive rate and speed. Among the all ensemble algorithm, the subspace discriminate ensemble was found the best method with the 100% accuracy, specificity, and sensitivity using 35 base classifiers. Subspace ensemble algorithm with principle component analysis and 4th scaling daubechies 4 wavelet filters produced the best performance. The main contribution of this work is that method has the potency of best classification of sEMG signal for elbow movement which can be beneficial for assistive robotic device development.

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Authors and Affiliations

  1. Electrical Engineering Department, National Institute of Technical Teachers Training and Research, Chandigarh, India

    Yogendra Narayan, Ram Murat Singh, Lini Mathew & S. Chatterji

Authors
  1. Yogendra Narayan
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  2. Ram Murat Singh
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  3. Lini Mathew
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  4. S. Chatterji
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Corresponding author

Correspondence to Yogendra Narayan .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Maharshi Dayanand University, Rohtak, Haryana, India

    Ashish Kumar Luhach

  2. Namibia University of Science and Technology, Windhoek, Namibia

    Dharm Singh

  3. National Chung Cheng University, Minxiong Township, Chiayi County, Taiwan

    Pao-Ann Hsiung

  4. Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Kamarul Bin Ghazali Hawari

  5. Saint Mary's University, Halifax, NS, Canada

    Pawan Lingras

  6. Department of Computer Science and Engineering, Jaypee University of Information Technology, Kandaghat, India

    Pradeep Kumar Singh

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Narayan, Y., Singh, R.M., Mathew, L., Chatterji, S. (2019). Surface EMG Signal Classification Using Ensemble Algorithm, PCA and DWT for Robot Control. In: Luhach, A., Singh, D., Hsiung, PA., Hawari, K., Lingras, P., Singh, P. (eds) Advanced Informatics for Computing Research. ICAICR 2018. Communications in Computer and Information Science, vol 955. Springer, Singapore. https://doi.org/10.1007/978-981-13-3140-4_20

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  • DOI: https://doi.org/10.1007/978-981-13-3140-4_20

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-3139-8

  • Online ISBN: 978-981-13-3140-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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