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Hybrid Brain-Computer Interface (BCI) based on the EEG and EOG signals

Issue title: Frontiers in Biomedical Engineering and Biotechnology – Proceedings of the 3rd International Conference on Biomedical Engineering and Biotechnology, 25–28 September 2014, Beijing, China

Article type: Research Article

Authors: Jiang, Jun | Zhou, Zongtan | Yin, Erwei | Yu, Yang | Hu, Dewen;

Affiliations: Department of Automatic Control, College of Mechatronics and Automation, National University of Defense Technology, 410073, Changsha, Hunan, People's Republic of China. E-mail: [email protected]

Note: [] Corresponding author. De-Wen Hu, Department of Automatic Control, College of Mechatronics and Automation (National University of Defense Technology), Hunan Province, Changsha 410073, China. Tel.: +86 731 84574977; Fax: +86 731 84574992; E-mail: [email protected]

Keywords: hybrid brain computer interface, EEG, EOG, event-related (de)synchronization, target selection

DOI: 10.3233/BME-141111

Journal: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 2919-2925, 2014

Published: 2014
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Abstract

Recently, the integration of different electrophysiological signals into an electroencephalogram (EEG) has become an effective approach to improve the practicality of brain-computer interface (BCI) systems, referred to as hybrid BCIs. In this paper, a hybrid BCI was designed by combining an EEG with electrocardiograph (EOG) signals and tested using a target selection experiment. Gaze direction from the EOG and the event-related (de)synchronization (ERD/ERS) induced by motor imagery from the EEG were simultaneously detected as the output of the BCI system. The target selection mechanism was based on the synthesis of the gaze direction and ERD activity. When an ERD activity was detected, the target corresponding to the gaze direction was selected; without ERD activity, no target was selected, even when a subjects gaze was directed at the target. With this mechanism, the operation of the BCI system is more flexible and voluntary. The accuracy and completion time of the target selection tasks during the online testing were 89.3% and 2.4 seconds, respectively. These results show the feasibility and practicality of this hybrid BCI system, which can potentially be used in the rehabilitation of disabled individuals.

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