P300 brainwave extraction from EEG signals: An unsupervised approach

作者：

Highlights：

• A novel unsupervised classifier of the P300 presence based on a match filter is proposed.

• With the combination of different artifact cancellation methods and P300 extraction techniques.

• This innovation brings a notable impact in ERP-based communicators.

• Database from a Donchin ERP-based speller is investigated.

摘要

•A novel unsupervised classifier of the P300 presence based on a match filter is proposed.•With the combination of different artifact cancellation methods and P300 extraction techniques.•This innovation brings a notable impact in ERP-based communicators.•Database from a Donchin ERP-based speller is investigated.

论文关键词：EEG,ERP,Artifacts,P300 classification,Matched filters,ICA

论文评审过程：Received 28 October 2016, Revised 28 December 2016, Accepted 29 December 2016, Available online 3 January 2017, Version of Record 7 January 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.12.038