Implementing a fuzzy inference system in a multi-objective EEG channel selection model for imagined speech classification

作者：

Highlights：

• It was searched the minimal subset of channels for imagined speech.

• Channel selection was approached as multi-objective to obtain a Pareto front.

• A fuzzy system inference was applied to find a promising solution from Pareto front.

• Channel selection had a statistically similar performance to the use of all channels.

• It was observed a dependence between features and classes of imagined speech.

摘要

•It was searched the minimal subset of channels for imagined speech.•Channel selection was approached as multi-objective to obtain a Pareto front.•A fuzzy system inference was applied to find a promising solution from Pareto front.•Channel selection had a statistically similar performance to the use of all channels.•It was observed a dependence between features and classes of imagined speech.

论文关键词：Brain-computer interfaces (BCI),Electroencephalograms (EEG),Imagined speech,Fuzzy inference system (FIS),Channel selection,Classification

论文评审过程：Received 9 June 2015, Revised 7 April 2016, Accepted 8 April 2016, Available online 19 April 2016, Version of Record 26 April 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.04.011