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Electromyogram (EMG) signal can be defined as the electrical activity of muscles cells. It is commonly used in motion recognition, treatment of neuromuscular disorders and prosthetic hand control. In this study, classification of EMG signals obtained from 6 different hand shapes of holding object was proposed. At first Short Time Fourier Transform of the EMG signal were evaluated to obtain their Time-Frekans...
In this paper an intelligent method called adaptive neuro-fuzzy inference system (ANFIS) is proposed for discriminating normal actions from aggressive actions using the features extracted from electromyography (EMG) signals. Classification of normal and aggressive actions are essential for diseases and prosthetic arm controls. But accurate classification of physical actions are sometimes not possible...
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