Development of electroencephalographic pattern classifiers for real and imaginary thumb and index finger movements of one hand

作者：

Highlights：

• Decoding accuracy of real and imaginary finger movements was explored by ANN and SVM.

• Real and imaginary movement of thumb/index fingers of one hand was used for decoding.

• The SVM was better for trial accumulation, ANN - for single-trial discrimination.

• Decoding of imagined movements through individual time intervals is promising for BCI.

摘要

•Decoding accuracy of real and imaginary finger movements was explored by ANN and SVM.•Real and imaginary movement of thumb/index fingers of one hand was used for decoding.•The SVM was better for trial accumulation, ANN - for single-trial discrimination.•Decoding of imagined movements through individual time intervals is promising for BCI.

论文关键词：Electroencephalography,Symbolic regression,Support vector machine,Artificial neural network,Motor imagery,Finger movements,Brain–computer interface

论文评审过程：Received 17 February 2014, Revised 8 December 2014, Accepted 9 December 2014, Available online 18 December 2014.

论文官网地址：https://doi.org/10.1016/j.artmed.2014.12.006