Title :
Hand motion detection from EMG signals by using ANN based classifier for human computer interaction
Author :
Ahsan, Md R. ; Ibrahimy, Muhammad I. ; Khalifa, Othman O.
Author_Institution :
Dept. of Electr. & Comput. Eng., Int. Islamic Univ. Malaysia, Kuala Lumpur, Malaysia
Abstract :
Today´s advanced muscular sensing and processing technologies have made the acquisition of electromyography (EMG) signal which is valuable. EMG signal is the measurement of electrical potentials generated by muscle cells which is an indicator of muscle activity. Other than rehabilitation engineering and clinical applications, EMG signals can also be employed in the field of human computer interaction (HCI) system. In this work, the detection of different hand movements (left, right, up and down) was obtained using artificial neural network (ANN). A back-propagation (BP) network with Levenberg-Marquardt training algorithm was utilized. The conventional time and time-frequency based feature sets have been chosen to train the neural network. The simulation results show that the designed network is able to recognize hand movements with satisfied classification efficiency in average of 88.4%.
Keywords :
backpropagation; electromyography; gesture recognition; human computer interaction; medical signal processing; neural nets; signal classification; ANN based classifier; BP network; EMG signal; HCI system; Levenberg-Marquardt training algorithm; artificial neural network; back-propagation network; electrical potential; electromyography; hand motion detection; human computer interaction; muscle cells; time-frequency based feature sets; Artificial neural networks; Electromyography; Feature extraction; Neurons; Noise; Support vector machine classification; Training; Artificial Neural Network; Back-Propagation; Discrete Wavelet Transform; Electromyography; Human Computer Interaction;
Conference_Titel :
Modeling, Simulation and Applied Optimization (ICMSAO), 2011 4th International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4577-0003-3
DOI :
10.1109/ICMSAO.2011.5775536
