Part of the Electrical and Computer Engineering Commons

Works by Stephen D. Hickman in Electrical and Computer Engineering

2016

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

2015

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

Link

2014

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

Link