Identification of Hand Movements based on MMG and EMG Signals

@inproceedings{Prociow2008IdentificationOH,
  title={Identification of Hand Movements based on MMG and EMG Signals},
  author={Pawel Prociow and Andrzej Wolczowski and Tito G. B. Amaral and Oct{\'a}vio P{\'a}scoa Dias and Joaquim Filipe},
  booktitle={BIOSIGNALS},
  year={2008}
}
This paper proposes a methodology that analysis and classifies the EMG and MMG signals using neural networks to control prosthetic members. Finger motions discrimination is the key problem in this study. Thus the emphasis is put on myoelectric signal processing approaches in this paper. The EMG and MMG signals classification system was established using the LVQ neural network. The experimental results show a promising performance in classification of motions based on both EMG and MMG patterns. 

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References

Publications referenced by this paper.
SHOWING 1-10 OF 11 REFERENCES

Measurement stand for recording EMG signals

K. Krysztoforski, A. Wołczowski
  • 2005

Measurement stand for recording EMG signals . Adv. of Robotics: Industrial and medical robotic systems, WKL, Warsaw

K. Krysztoforski, A Wołczowski
  • 2005

Functional mapping of multiple mechanomyographic signals to hand kinematics

  • Canadian Conference on Electrical and Computer Engineering 2004 (IEEE Cat. No.04CH37513)
  • 2004

MMG-based classification of muscle activity for prosthesis control

  • The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
  • 2004

Smart Hand: The Concept of Sensor based Control

A. Wołczowski
  • Proc. of 7th IEEE Int. Symp. on ‘Methods and Models in Automation and Robotics’,
  • 2001

A combination of AR and neural network technique for EMG pattern identification

  • Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
  • 1996

Self-Organizing Maps, Springer, Berlin

Kohonen, K Teuvo
  • 1995