| Paper Abstract and Keywords |
| Presentation |
2013-07-18 16:30
Basic Study on Auditory ERP-Based Brain-Machine Interface Natsumi Ishido (NAIST), Takeshi Ogawa, Satoshi Morimoto, Atsunori Kanemura, Masaki Maruyama, Motoaki Kawanabe (ATR), Shin Ishii (Kyoto Univ.), Hiroshi Saruwatari, Satoshi Nakamura, Kiyohiro Shikano (NAIST) EA2013-42 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
In recent years, Brain-Machine Interface (BMI), which is a direct communication pathway between the brain and
an external device, has been expected as a method to control electrical appliances without using hands or any other body parts.
However, since the most of past experiments were only held in restrictive conditions, it is necessary to develop a BMI system
that can perform well even if subjects are in a natural daily environment. On the other hands, previous ERP studies showed
that, during an oddball paradigm, a large positive ERP component, the P300, arose more than 300 ms after the onset of the
attended beep. In this study, we consider that the auditory P300 would be useful for daily BMI because people often focus
upon the appliances when they want to use them. We conduct the experiment with an oddball paradigm in the experimental
facility imitating the actual living environment. In the experiment, we present three kinds of beep stimuli, and subjects are
instructed to attend and count the number of target. We classify the averaged P300 by using Linear Discriminant Analysis.
There were significant differences between target ERP data and non-target ERP data. Through our research, we confirm the
usefulness of auditory ERP-based BMI in the daily environment. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
BMI / ERP / P300 / Auditory attention / / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 113, no. 134, EA2013-42, pp. 51-56, July 2013. |
| Paper # |
EA2013-42 |
| Date of Issue |
2013-07-11 (EA) |
| ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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EA2013-42 |