A Study of Electromyogram Based on Human-Computer Interface

In this paper, a new control system based on forearm electromyogram (EMG) is proposed for computer peripheral control and artificial prosthesis control. This control system intends to realize the commands of six pre-defined hand poses: up, down, left, right, yes, and no. In order to research the possibility of using a unified amplifier for both electro- encephalogram (EEG) and EMG, the surface forearm EMG data is acquired by a 4-channel EEG measure- ment system. The Bayesian classifier is used to classify the power spectral density (PSD) of the signal. The experiment result verifies that this control system can supply a high command recognition rate (average 48%) even the EMG data is collected with an EEG system just with single electrode measurement.

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