Reliable EOG signal-based control approach with EEG signal judgment

Abstract

This article proposes a reliable EOG signal-based control approach with EEG signal judgment. In this method, raw bio-neurological signals (including EOG and EEG) are first extracted and segmented in the pre-processing stage. The processed bio-neurological signals will then be evaluated by calculating the feature parameters of these signals. Since the feature parameters in bio-neurological signals may be contaminated by various kinds of artifacts, some artifacts of bio-neurological signals can be indicated by means of the feature parameters of bio-neurological signals. Therefore, the bio-neurological signals contaminated with artifacts cannot be adopted to generate control signals or to judge the correctness of control signals. In the proposed method, in order to generate a reliable control signal based on the EOG signal, the EEG signal is adopted to assist in making a judgment about the validity of the EOG signal. With the proposed method, an EOG signal-based control software platform has been implemented. By using this platform, simulation work has been carried out to control the behavior of a robot. The simulation results verified the effectiveness of the proposed method.