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.
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This work was presented in part and was awarded the Best Paper Award at the 14th International Symposium on Artificial Life and Robotics, Oita, Japan, February 5–7, 2009
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Zhang, T., Chen, C. & Nakamura, M. Reliable EOG signal-based control approach with EEG signal judgment. Artif Life Robotics 14, 195 (2009). https://doi.org/10.1007/s10015-009-0652-7
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DOI: https://doi.org/10.1007/s10015-009-0652-7