Identification of motion from multi-channel EMG signals for control of prosthetic hand

@article{Geethanjali2011IdentificationOM,
  title={Identification of motion from multi-channel EMG signals for control of prosthetic hand},
  author={P. Geethanjali and Kamala Kanta Ray},
  journal={Australasian Physical & Engineering Sciences in Medicine},
  year={2011},
  volume={34},
  pages={419-427}
}
The authors in this paper propose an effective and efficient pattern recognition technique from four channel electromyogram (EMG) signals for control of multifunction prosthetic hand. Time domain features such as mean absolute value, number of zero crossings, number of slope sign changes and waveform length are considered for pattern recognition. The patterns are classified using simple logistic regression (SLR) technique and decision tree (DT) using J48 algorithm. In this study six specific… CONTINUE READING
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Classification of low level surface electromyogram using independent component analysis

  • GR Naik, DK Kumar, M Palanizwami
  • IET Signal Process
  • 2010
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