Analysis and classification of forearm muscles activities during gripping using EMG signals

Abstract

Electromyography (EMG) is the recording about the electrical activity of muscle tissue. EMG measures the electrical signal that generated from the muscles during contraction or relaxation action. It has been used in various fields such as medical diagnosis and engineering applications. In this research, EMG signals were recorded from three forearm muscles to analyze and classify forearm muscles activities during gripping. EMG signals were measured from the subjects by applying three different values of grip force. Features such as root mean square, mean absolute value, standard deviation and variances are extracted from the acquired EMG signals. The values of these features were used for the classification in different level of grip strength. The results show that EMG signals’ amplitude and frequency from the forearm muscles increased due to the increase of grip strength and different levels of grip force can be classified from the three forearm muscles’ activities.