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Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015 pp 565–575Cite as

Hilbert–Huang Transform Applied to the Recognition of Multimodal Biosignals in the Control of Bioprosthetic Hand

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 403))

Abstract

This paper deals with the problem of bioprosthetic hand control via recognition of user intent on the basis of electromyography (EMG) and mechanomyography (MMG) signals acquired from the surface of a forearm. As a method of signal parameterization the Hilbert–Huang (HH) transform is applied which is an effective tool for reduction of feature space dimension. The performance of proposed recognition method based on HH transform of EMG and MMG signals was experimentally compared against an autoregressive model of dimensionality reduction using real data concerning the recognition of five types of grasping movements. The experimental results show that the HH transform approach with root mean square of amplitude feature outperforms an autoregressive method.

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Acknowledgments

This work was financed from the National Science Center resources in 2012–2014 years as a research project No ST6/06168 and supported by the statutory funds of the Department of Systems and Computer Networks, Wroclaw University of Technology.

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Authors and Affiliations

  1. Department of Systems and Computer Networks, Wroclaw University of Technology, Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Edward Puchala, Maciej Krysmann & Marek Kurzyński

Authors
  1. Edward Puchala
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  2. Maciej Krysmann
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  3. Marek Kurzyński
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Corresponding author

Correspondence to Edward Puchala .

Editor information

Editors and Affiliations

  1. Department of Systems, Wrocław University of Technology, Wroclaw, Poland

    Robert Burduk

  2. Department of Systems and Computer, Wrocław University of Technology, Wroclaw, Poland

    Konrad Jackowski

  3. Department of Systems and Computer, Wrocław University of Technology, Wroclaw, Poland

    Marek Kurzyński

  4. Dept. of Systems and Computer Networks, Wrocław University of Technology, Wroclaw, Poland

    Michał Woźniak

  5. Department of Systems, Wrocław University of Technology, Wroclaw, Poland

    Andrzej Żołnierek

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Puchala, E., Krysmann, M., Kurzyński, M. (2016). Hilbert–Huang Transform Applied to the Recognition of Multimodal Biosignals in the Control of Bioprosthetic Hand. In: Burduk, R., Jackowski, K., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds) Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015. Advances in Intelligent Systems and Computing, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-319-26227-7_53

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  • DOI: https://doi.org/10.1007/978-3-319-26227-7_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26225-3

  • Online ISBN: 978-3-319-26227-7

  • eBook Packages: EngineeringEngineering (R0)

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