Elucidation of brain activities by electroencephalograms and its application to brain computer interface


YAMANOİ T.

46th IEEE International Symposium on Multiple-Valued Logic, ISMVL 2016, Sapporo, Hokkaido, Japan, 18 - 20 May 2016, vol.2016-July, pp.1-4, (Full Text) identifier identifier

  • Nəşrin Növü: Conference Paper / Full Text
  • Cild: 2016-July
  • Doi nömrəsi: 10.1109/ismvl.2016.45
  • Çap olunduğu şəhər: Sapporo, Hokkaido
  • Ölkə: Japan
  • Səhifə sayı: pp.1-4
  • Açar sözlər: brain computer interface, canonical discriminant analysis, image of robot movement, image recognition, single trial EEG
  • Açıq Arxiv Kolleksiyası: Konfrans Materialı
  • Adres: Bəli

Qısa məlumat

In order to develop a brain computer interface (BCI), the present author and his group, yamanoi group, have investigated the brain activity during human recognition of characters and symbols representing directional meaning. Subjects were asked to read them silently. Electroencephalograms (EEGs) were averaged for each stimulus type, and event related potentials (ERPs) were obtained. The equivalent current dipole source localization (ECDL) method has been applied to these ERPs. In both cases, ECDs were localized to areas related to the working memory for spatial perception, i. e. the right upper or the right middle frontal areas. And the opposite directional arrows had opposite dipoles in these areas. Taking into account these facts, the group recorded EEGs from subjects looking and recalling ten types of images of robot movement presented on a CRT. The group investigated a single trial EEGs of the subject precisely after the latency at 400 ms, and determined effective sampling latencies for the discriminant analysis to ten types of images. They sampled EEG data at latencies from 400 ms to 900 ms at 25 ms intervals by the four channels such as Fp2, F4, C4 and F8. Results of the discriminant analysis with jack knife (cross validation) method for ten type objective varieties, the discriminant rates for three subjects were almost 90 %. We could control a micro robot with ten commands only to recall corresponding movement image.