EMG Based Classification of Percentage of Maximum Voluntary Contraction Using Artificial Neural Networks, Stephen D. Hickman, Rocio Alba-Flores, Mohammad Ahad
Mohammad Ahad

EMG Based Classification of Percentage of Maximum Voluntary Contraction Using Artificial Neural Networks, Stephen D. Hickman, Rocio Alba-Flores, Mohammad Ahad
Rocio Alba-Flores

A Case Study on Tuning Artificial Neural Networks to Recognize Signal Patterns of Hand Motions, Stephen D. Hickman, Arash S. Mirzakhani, J. Pabon, Rocio Alba-Flores
Rocio Alba-Flores

A Case Study on Tuning Artificial Neural Networks to Recognize Signal Patterns of Hand Motions, Stephen D. Hickman, Arash S. Mirzakhani, J. Pabon, Rocio Alba-Flores
Rocio Alba-Flores

EMG Based Classification of Percentage of Maximum Voluntary Contraction Using Artificial Neural Networks, Stephen D. Hickman, Rocio Alba-Flores, Mohammad Ahad
Rocio Alba-Flores

A Case Study on Tuning Artificial Neural Networks to Recognize Signal Patterns of Hand Motions, Stephen D. Hickman, Arash S. Mirzakhani, J. Pabon, Rocio Alba-Flores
Department of Electrical & Computer Engineering Faculty Research & Publications

EMG Based Classification of Hand Motions for Use in Robotics and Prosthetics, Stephen D. Hickman
GS4 Georgia Southern Student Scholarship Symposium

Classification of Surface EMG Signals with Respect to Percent Maximum Voluntary Contraction Using Artificial Neural Networks, Stephen D. Hickman
Georgia Undergraduate Research Conference (2014-2015)

EMG Based Classification of Percentage of Maximum Voluntary Contraction Using Artificial Neural Networks, Stephen D. Hickman, Rocio Alba-Flores, Mohammad Ahad
Department of Electrical & Computer Engineering Faculty Research & Publications