International Journal of Industrial Electronics and Electrical Engineering(IJIEEE).
Paper Title - Sign Language Recognition Based On Electromyography (EMG) Signal Using Artificial Neural Network (ANN)
EMG signal is a muscular signal. It can represent equally time & frequency domain. EMG provides measurement
of muscular performance. Hence it is a direct representation of strength of health. It is used for identification & treatment
tasks by comparing with normal person. EMG biofeedback can be instantaneous as compare to manual inspection. EMG
signal used in management of prostheses & to improve the effectiveness of rehabilitation robotics. The motive of this paper
is to describe the process of detecting different predefined hand gestures using artificial neural network (ANN).This different
hand gestures used by deaf & dumb people to understand the things. The EMG sample signatures are extracted from the
signals for all movement and then given to ANN for training & classification. A back-propagation (BP) network has been
used for the recognition of sign, as it works well for different biosignal. The features like autoregression coefficient, fast
Fourier transform, short time Fourier transform, wavelet transform coefficient, mean absolute value, root mean square,
variance, standard deviation, Mean frequency, zero crossing and slope sign change are selected to train the neural network.
Author - V.T.Gaikwad, M.M.Sardeshmukh
Citation - V.T.Gaikwad ,
V.T.Gaikwad, M.M.Sardeshmukh " Sign Language Recognition Based On Electromyography (EMG) Signal Using Artificial Neural Network (ANN) " ,
International Journal of Industrial Electronics and Electrical Engineering , Volume-2,Issue-6 ( Jun, 2014 )