An Examination of EEG Frequency Components Related to Speech Imagery and Its Identification

Tsukahara, Akihiko; Yamada, Masayuki; Tanaka, Keita; Uchikawa, Y.

doi:10.1541/ieejeiss.139.588

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2020

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“…Speech can be recalled intuitively and does not require special training 8 ; one can think that discrimination between recalled syllables and world might be useful. The authors previously examined EEG components associated with speech imagery of “I want to drink,” and reported on features of these EEG components 9 . Extraction of such features is promising in terms of input signals for BMI.…”

Section: Introductionmentioning

confidence: 99%

A design of EEGNet‐based inference processor for pattern recognition of EEG using FPGA

Tsukahara¹,

Anzai

Tanaka

et al. 2020

Elect Comm in Japan

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In recent years, brain‐machine interface (BMI) is attracting attention. BMI is a technology that enables machine operation using biological signals such as EEG. For further advancement of BMI technology, there is a need for advanced BMI devices. Therefore, the purpose of this study is development of BMI hardware specialized for handling EEG as an interface for human adaptive mechatronics (HAM) that know human's state and operate according to the state. As one of the examinations, we are constructing a pattern recognition processor for EEG in real time on Field Programmable Gate Array (FPGA), which is an LSI that can reconfigure the processor. This paper reports on the designed EEGNet processor and the result of logic circuit simulation and implementation.

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Section: Introductionmentioning

confidence: 99%