Imagined Speech Classification with EEG Signals for Silent Communication: A Preliminary Investigation into Synthetic Telepathy

摘要：

The objective of this work is to explore the potential use of electroencephalography (EEG) as a means for silent communication by way of decoding imagined speech from measured electrical brain waves. EEG signals were recorded at University of California, Irvine (UCI) from 7 volunteer subjects imagining two syllables, /ba/and /ku/, without speaking or performing any overt actions. Our goal is to classify these imagined syllables and based on the resulting accuracy assess the feasibility of this task. In this research, the EEG data are preprocessed to reduce the effects of artifacts and noise, and autoregressive (AR) coefficients are extracted as features for imagined syllable classification using a k-Nearest Neighbor classifier. Initial results suggest that it is possible to identify imagined speech.

作者: Katharine Brigham B.V.K.Vijaya Kumar

作者单位: Department of Electrical and Computer Engineering Carnegie Mellon University, Pittsburgh, PA, USA

会议类型: 国际会议

会议名称: The 4th International Conference on Bioinformatics and Biomedical Engineering(第四届IEEE生物信息与生物医学工程国际会议 iCBBE 2010)

会议地点: 成都

会议语种:英文

页码: 1-4

在线出版日期: 2010-06-18（万方平台首次上网日期，不代表论文的发表时间）