Multiclass Myoelectric Identification of Five Fingers Motion using Artificial Neural Network and Support Vector Machine-Reference-Cited by-同舟云学术

Multiclass Myoelectric Identification of Five Fingers Motion using Artificial Neural Network and Support Vector Machine

Published:2017-07 Issue:3 Volume:2 Page:1026-1033
ISSN:2415-6698
Container-title:Advances in Science, Technology and Engineering Systems Journal
language:
Short-container-title:Adv. sci. technol. eng. syst. j.

Author:

Ahmad Jawad,Butt Ammar Mohsin,Riaz Muhammad Tanveer,Bhutta Shoaib,Khan Muhammad Zeeshan,Ul-Haq Inam

Publisher

ASTES Journal

Subject

Management of Technology and Innovation,Physics and Astronomy (miscellaneous),Engineering (miscellaneous)

Link

http://www.astesj.com/publications/ASTESJ_0203130.pdf

Reference11 articles.

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3. B. Crawford, K. Miller, P. Shenoy, and R. Rao, "Real-time classification of electromyographic signals for robotic control," Proc. 20th Nat. Conf. Artificial Intell. (AAAI 05), 2006, pp. 523-528.

4. M.R. Ahsan, M.I. Ibrahimy, O.O. Khalifa, "Hand Motion Detection from EMG Signals by Using ANN based Classifier for Human," Computer Interaction, Modeling, Simulation and Applied Optimization (ICMSAO), 2011 4th International Conference on , pp.1-6, April 2011.

5. M.R. Ahsan, M.I. Ibrahimy, O.O. Khalifa, "Electromygraphy (EMG) Signal based Hand Gesture Recognition using Artificial Neural Network (ANN),"Mechatronics (ICOM), 2011 4th International Conference On , pp.1-6, May 2011.

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