Design and Implementation of Myoelectric Controlled Arm
Tariq M. Younes1, Mohammad A. AlKhedher2, Abdel-Hamid Soliman3 & Aiman Al Alawin1 Show affiliations
- Al Balqa Applied University, Jordan
- Abu Dhabi University, United Arab Emirates
- Staffordshire University, United Kingdom
Journal of Mechatronics and Robotics, Volume 3, Issue 1, pp. 552–562 · doi.org/10.3844/jmrsp.2019.552.562
Abstract
In this study a discrimination system, using a neural network for Electromyogram (EMG) externally controlled Arm is proposed. In this system, the Artificial Neural Network (ANN) is used to learn the relation between the power spectrum of EMG signal analysed by Fast Fourier Transform (FFT) and the performance desired by handicapped people. The Neural Network can discriminate 4 performances of the EMG signals simultaneously. The digital signal processing was realized using MATLAB and LabVIEW software.
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Younes, T. M., AlKhedher, M. A., Soliman, A. & Al Alawin, A. (2019). Design and Implementation of Myoelectric Controlled Arm. Journal of Mechatronics and Robotics, 3(1), 552–562. https://doi.org/10.3844/jmrsp.2019.552.562
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