Publication: Improvement of Motor Imagery BCI using Silent Speech
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Issued Date
2020-06-01
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2-s2.0-85091823337
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Mahidol University
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SCOPUS
Bibliographic Citation
17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2020. (2020), 840-843
Suggested Citation
Sansit Ngamrassameewong, Vichaya Manatchinapisit, Yodchanan Wongsawat Improvement of Motor Imagery BCI using Silent Speech. 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2020. (2020), 840-843. doi:10.1109/ECTI-CON49241.2020.9158081 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/59950
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Improvement of Motor Imagery BCI using Silent Speech
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Abstract
© 2020 IEEE. Human expression are exhibited throughout by language, which is generally used for communications. Making use of this fact, combining the language expression silently with the imagination of movement may lead to the improvement on developing the brain-computer interface (BCI) system. This paper focuses on the silent speech related to upper limbs movement. In the experiment, five subjects performed silent speech, i.e. at the same time, imagined upper limbs movement follow by two words, which are "RIGHT"or "LEFT". Furthermore, each of the participants performed another experiment doing only motor imagery (MI). In both experiments, there are five trials for each movement side. 19-channel EEG was recorded. The EEG signals were simply analyzed by using the absolute power. The result shows the clearer activation of event-related desynchronization (ERD) of the alpha band (8-12 Hz) on the motor area (C3, C4) during the combination of silent speech and MI.