SCIENCE@home

Wavelet-based detection on MUAPs decomposed from sEMG under different levels of muscle isometric contraction

Ziyou Li,Qichuan Ding,Xingang Zhao,Jianda Han,Guangjun Liu

Published 2017 in IEEE International Conference on Robotics and Biomimetics

ABSTRACT

Decomposition of EMG (electromyography), in which the MUAPs (Motor Units Action Potentials) are extracted from the original EMG signals, is a useful approach for evaluating the physiological properties of muscles and studying the neural mechanism of human motions. Existing decomposition methods usually extracted the MUAPs via the waveform matching between the detected spikes and MUAP templates. However, those methods always involve too many artificial parameters and have no generally mathematical expression, which make them inflexible in practical applications and also cause poor robustness under interference. With respect to the problem, in this paper, a wavelet-based decomposition method is proposed to detect the “true” MUAPs from sEMG. Two standard Gaussian wavelets are firstly defined as the basic MUAP expressions; then, wavelet transform is performed to describe scales and magnitudes of different MUAPs from different nerve fibers. Experiments were conducted to verify the performance of the proposed method, where MUAPs decomposed from sEMG under different levels of muscle contraction can be effectively detected by the method.

PUBLICATION RECORD

  • Publication year

    2017

  • Venue

    IEEE International Conference on Robotics and Biomimetics

  • Publication date

    2017-12-01

  • Fields of study

    Medicine, Computer Science, Engineering

  • Identifiers
    DOI 10.1109/ROBIO.2017.8324542
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-16 of 16 references · Page 1 of 1

CITED BY