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HHT Based Features for Discrimination of EMG Signals

  • Gaurav Sahu
  • Nishant Chaurasia
  • Prem Prakash Suwalka
  • Varun Bajaj
  • Anil Kumar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 340)

Abstract

A new method based on Hilbert-Huang transform (HHT) is proposed for discrimination of electromyogram (EMG) signals. The HHT consists of two steps namely empirical mode decomposition (EMD) and the Hilbert transform (HT). The EMD decomposes EMG signal into set of narrow-band intrinsic mode functions (IMFs) and the Hilbert transformation of these IMFs provide analytic IMFs. The bandwidth due to amplitude modulation (\( B_{AM} \)) and bandwidth due to frequency modulation (\( B_{FM} \)) estimation of analytic IMFs have been used as a feature for discrimination of myopathy, neuropathy, and healthy EMG signals. The bandwidth features are very effective to discriminate myopathy, neuropathy, and healthy EMG signals. The experimental results show the effectiveness of the proposed method for discrimination of myopathy, neuropathy, and healthy EMG signals.

Keywords

EMG signal Myopathy Neuropathy Hilbert-Huang transform 

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Copyright information

© Springer India 2015

Authors and Affiliations

  • Gaurav Sahu
    • 1
  • Nishant Chaurasia
    • 1
  • Prem Prakash Suwalka
    • 1
  • Varun Bajaj
    • 1
  • Anil Kumar
    • 1
  1. 1.Discipline of Electronics and Communication EngineeringPDPM Indian Institute of Information Technology, Design and Manufacturing JabalpurJabalpurIndia

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