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Statistical Methods and Artificial Neural Networks Techniques in Electromyography

Author

Listed:
  • Ahmad Taher Azar

    (Benha University, Egypt)

  • Valentina E. Balas

    (University of Arad, Romania)

Abstract

This work represents a comparative study for the activity of the masseter muscle for patients before trial base denture insertion and the activity of the same muscle after trial denture base insertion for both right and left masseter muscles. The study tried to find if there were significant differences in the activity of the masseter muscle before and after patients wearing their trial denture base using two approaches: parametric statistical methods and a Neural Network Classifier. Statistical analysis was performed on three feature vectors extracted from autoregressive (AR) modeling, Discrete Wavelet Transform (WT), and from Wavelet Packet Transform (WP). The least significant difference test and the student t-test have not proved significant differences in the masseter muscle activity before and after wearing denture. However, using the same feature vectors, a neural network classifier has proved that there are significant differences in the masseter muscle activity before and after patients wearing trial denture base.

Suggested Citation

  • Ahmad Taher Azar & Valentina E. Balas, 2012. "Statistical Methods and Artificial Neural Networks Techniques in Electromyography," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 1(1), pages 39-47, January.
  • Handle: RePEc:igg:jsda00:v:1:y:2012:i:1:p:39-47
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