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Brain Machine Interface Technology Enabling Control of Machine by Human Thought Alone

Article of Honda R&D Technical Review Vol.22 No.2

Summary

Recently, brain machine interface (BMI) technology has gathered a lot of attention in regard to controlling a machine without any physical devices. Although this interface is often seen in science fiction, it is becoming realistic due to dramatic progress in brain and computer science. By directly connecting a human's brain with a machine, a machine can be controlled by human thought alone.
Honda has challenged the development of this BMI in collaboration with ATR and Shimadzu. By developing a new brain measurement using electroencephalography (EEG) and near-infrared spectroscopy (NIRS) and applying sparse logistic regression into BMI to detect a human's intention correctly, we successfully developed a highly accurate interface of BMI.
To validate our BMI system, we used 4-motor imagery task often used in BMI research. The performance of our BMI is more than 90% accuracy. This result is competitive against other BMI research groups.

Reference

(1) Dornhege, G., Millan, J. R., Hinterberger, T., McFarland, D. J., Muller, K.: Toward Brain-Computer Interfacing, The MIT Press (2007)
(2) Wessberg, J., Stambaugh, C. R., Kralik, J. D., Beck, P. D., Laubach, M., Chapin, J. K., Kim, J., Biggs, S. J., Srinivasan, M. A., Nicolelis, M. A.: Real-time prediction of hand trajectory by ensembles of cortical neurons in primates, Nature, 408, p. 361-365 (2000)
(3) Kawato, M.: Brain Network Interface, Journal of the institute of electronics, Information and communication engineers, 91[2], p. 123-130 (2008) (in Japanese)
(4) Kamitani, Y., Tong, F.: Decoding the visual and subjective contents of the human brain, Nat Neurosci, 8(5), p. 679-685 (2005)
(5) http://www.honda.co.jp/news/2006/c060524a.html
(6) Ichijo, S. Takahashi, K.: The 101 chapters for reading electroencephalography, Igaku-Shoin (2003) (in Japanese)
(7) http://www.an.shimadzu.co.jp/prt/nirs/nirs_top.html
(8) Yamashita, O., Sato, M., Yoshioka, T., Tong, F., Kamitani, Y.: Sparse estimation automatically selects voxels relevant for the decoding of fMRI activity patterns, Neuroimage, 42, p. 1414-1429 (2008)

Author (organization or company)

Tatsuya OKABE(Fundamental Technology Research Center)、Kentaro YAMADA(Fundamental Technology Research Center)、Masahiro KIMURA(Fundamental Technology Research Center)、Akihiro TODA(Fundamental Technology Research Center)、Masaaki SATO(Advanced Telecommunications Research Institute International Computational Neuroscience Laboratories)、Okito YAMASHITA(Advanced Telecommunications Research Institute International Computational Neuroscience Laboratories)、Yusuke TAKEDA(Advanced Telecommunications Research Institute International Computational Neuroscience Laboratories)、Mitsuo KAWATO(Advanced Telecommunications Research Institute International Computational Neuroscience Laboratories)

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