한빛사논문
- 조회483
Ji-Hoon Jeong , Associate Member, IEEE, Jeong-Hyun Cho , Byeong-Hoo Lee , and Seong-Whan Lee , Fellow, IEEE
Ji-Hoon Jeong is with the School of Computer Science, Chungbuk National University, Cheongju 28644, Chungbuk, South Korea
Jeong-Hyun Cho and Byeong-Hoo Lee are with the Department of Brain and Cognitive Engineering, Korea University, Seoul 02841, South Korea
Seong-Whan Lee is with the Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea
Corresponding author: Seong-Whan Lee
Abstract
Electroencephalogram (EEG)-based brain-machine interface (BMI) has been utilized to help patients regain motor function and has recently been validated for its use in healthy people because of its ability to directly decipher human intentions. In particular, neurolinguistic research using EEGs has been investigated as an intuitive and naturalistic communication tool between humans and machines. In this study, the human mind directly decoded the neural languages based on speech imagery using the proposed deep neurolinguistic learning. Through real-time experiments, we evaluated whether BMI-based cooperative tasks between multiple users could be accomplished using a variety of neural languages. We successfully demonstrated a BMI system that allows a variety of scenarios, such as essential activity, collaborative play, and emotional interaction. This outcome presents a novel BMI frontier that can interact at the level of human-like intelligence in real time and extends the boundaries of the communication paradigm.
논문정보
- Research article
- 2022년 10월 (BRIC 등록일 2022-12-22)
- 국내 연구진
- 바이오·의료융합 > 뇌인지과학
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