EMG Signals classification based on singular value decomposition and neural network
نویسندگان
چکیده
The electromyogram (EMG) signal contains lots of information about muscular changes related muscular disorder such as myopathy. In this paper, we present a new method for classification of EMG signals based on singular value decomposition. The EMG signal represent in the matrix form, features extracted from the singular value decomposition and singular value of EMG signal used as features for classification. These features used as an input to back propagation neural network classifier for classification of EMG signals. The classification accuracy for classification of normal and myopathy EMG signals obtained by proposed method is 96.7. Simulation results illustrate the effectiveness of the proposed method.
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